Clémentine commited on
Commit
efeee6d
1 Parent(s): 9833cdb

updated leaderboard

Browse files
README.md CHANGED
@@ -8,7 +8,8 @@ sdk_version: 4.4.0
8
  app_file: app.py
9
  pinned: true
10
  license: apache-2.0
11
- duplicated_from: HuggingFaceH4/open_llm_leaderboard
12
  ---
13
 
14
  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
8
  app_file: app.py
9
  pinned: true
10
  license: apache-2.0
 
11
  ---
12
 
13
  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
14
+
15
+ Most of the variables to change for a default leaderboard are in env (replace the path for your leaderboard) and src/display/about.
app.py CHANGED
@@ -3,7 +3,7 @@ import pandas as pd
3
  from apscheduler.schedulers.background import BackgroundScheduler
4
  from huggingface_hub import snapshot_download
5
 
6
- from src.display.about import (
7
  CITATION_BUTTON_LABEL,
8
  CITATION_BUTTON_TEXT,
9
  EVALUATION_QUEUE_TEXT,
@@ -25,13 +25,13 @@ from src.display.utils import (
25
  WeightType,
26
  Precision
27
  )
28
- from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, H4_TOKEN, QUEUE_REPO, REPO_ID, RESULTS_REPO
29
  from src.populate import get_evaluation_queue_df, get_leaderboard_df
30
  from src.submission.submit import add_new_eval
31
 
32
 
33
  def restart_space():
34
- API.restart_space(repo_id=REPO_ID, token=H4_TOKEN)
35
 
36
  try:
37
  print(EVAL_REQUESTS_PATH)
@@ -91,8 +91,7 @@ def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
91
  return filtered_df
92
 
93
 
94
- def filter_queries(query: str, filtered_df: pd.DataFrame):
95
- """Added by Abishek"""
96
  final_df = []
97
  if query != "":
98
  queries = [q.strip() for q in query.split(";")]
 
3
  from apscheduler.schedulers.background import BackgroundScheduler
4
  from huggingface_hub import snapshot_download
5
 
6
+ from display.about import (
7
  CITATION_BUTTON_LABEL,
8
  CITATION_BUTTON_TEXT,
9
  EVALUATION_QUEUE_TEXT,
 
25
  WeightType,
26
  Precision
27
  )
28
+ from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, TOKEN, QUEUE_REPO, REPO_ID, RESULTS_REPO
29
  from src.populate import get_evaluation_queue_df, get_leaderboard_df
30
  from src.submission.submit import add_new_eval
31
 
32
 
33
  def restart_space():
34
+ API.restart_space(repo_id=REPO_ID, token=TOKEN)
35
 
36
  try:
37
  print(EVAL_REQUESTS_PATH)
 
91
  return filtered_df
92
 
93
 
94
+ def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame:
 
95
  final_df = []
96
  if query != "":
97
  queries = [q.strip() for q in query.split(";")]
src/display/about.py CHANGED
@@ -1,31 +1,33 @@
1
  from src.display.utils import ModelType
 
 
2
 
3
- # To complete, what is your leaderboard name
 
 
 
 
 
 
 
 
 
 
 
 
4
  TITLE = """<h1 align="center" id="space-title">Leaderboard</h1>"""
5
 
6
- # to complete - what does your leaderboard evaluate
7
  INTRODUCTION_TEXT = """
8
  """
9
 
10
- # to complete - which evaluations are you running? how can people reproduce what you have?
11
  LLM_BENCHMARKS_TEXT = f"""
12
  ## How it works
13
 
14
  ## Reproducibility
15
  To reproduce our results, here is the commands you can run:
16
 
17
- ## Quantization
18
- To get more information about quantization, see:
19
- - 8 bits: [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), [paper](https://arxiv.org/abs/2208.07339)
20
- - 4 bits: [blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes), [paper](https://arxiv.org/abs/2305.14314)
21
-
22
- ## Model types
23
- - {ModelType.PT.to_str(" : ")} model: new, base models, trained on a given corpora
24
- - {ModelType.FT.to_str(" : ")} model: pretrained models finetuned on more data
25
- Specific fine-tune subcategories (more adapted to chat):
26
- - {ModelType.IFT.to_str(" : ")} model: instruction fine-tunes, which are model fine-tuned specifically on datasets of task instruction
27
- - {ModelType.RL.to_str(" : ")} model: reinforcement fine-tunes, which usually change the model loss a bit with an added policy.
28
- If there is no icon, we have not uploaded the information on the model yet, feel free to open an issue with the model information!
29
  """
30
 
31
  EVALUATION_QUEUE_TEXT = """
 
1
  from src.display.utils import ModelType
2
+ from enum import Enum
3
+ from dataclasses import dataclass
4
 
5
+ @dataclass
6
+ class Task:
7
+ benchmark: str
8
+ metric: str
9
+ col_name: str
10
+
11
+ # Init: to update with your specific keys
12
+ class Tasks(Enum):
13
+ task0 = Task("Key in the harness", "metric in the harness", "Display name 1")
14
+ task1 = Task("Key in the harness", "metric in the harness", "Display name 2")
15
+
16
+
17
+ # Your leaderboard name
18
  TITLE = """<h1 align="center" id="space-title">Leaderboard</h1>"""
19
 
20
+ # What does your leaderboard evaluate?
21
  INTRODUCTION_TEXT = """
22
  """
23
 
24
+ # Which evaluations are you running? how can people reproduce what you have?
25
  LLM_BENCHMARKS_TEXT = f"""
26
  ## How it works
27
 
28
  ## Reproducibility
29
  To reproduce our results, here is the commands you can run:
30
 
 
 
 
 
 
 
 
 
 
 
 
 
31
  """
32
 
33
  EVALUATION_QUEUE_TEXT = """
src/display/utils.py CHANGED
@@ -3,21 +3,11 @@ from enum import Enum
3
 
4
  import pandas as pd
5
 
 
 
6
  def fields(raw_class):
7
  return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]
8
 
9
-
10
- @dataclass
11
- class Task:
12
- benchmark: str
13
- metric: str
14
- col_name: str
15
-
16
- # Init: to update with your specific keys
17
- class Tasks(Enum):
18
- task0 = Task("Key in the harness", "metric in the harness", "display name")
19
- task1 = Task("Key in the harness", "metric in the harness", "display name")
20
-
21
  # These classes are for user facing column names,
22
  # to avoid having to change them all around the code
23
  # when a modif is needed
@@ -30,6 +20,7 @@ class ColumnContent:
30
  never_hidden: bool = False
31
  dummy: bool = False
32
 
 
33
  auto_eval_column_dict = []
34
  # Init
35
  auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
@@ -54,6 +45,7 @@ auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("model_name_
54
  # We use make dataclass to dynamically fill the scores from Tasks
55
  AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
56
 
 
57
  @dataclass(frozen=True)
58
  class EvalQueueColumn: # Queue column
59
  model = ColumnContent("model", "markdown", True)
@@ -63,24 +55,7 @@ class EvalQueueColumn: # Queue column
63
  weight_type = ColumnContent("weight_type", "str", "Original")
64
  status = ColumnContent("status", "str", True)
65
 
66
- baseline_row = {
67
- AutoEvalColumn.model.name: "<p>Baseline</p>",
68
- AutoEvalColumn.revision.name: "N/A",
69
- AutoEvalColumn.precision.name: None,
70
- AutoEvalColumn.average.name: 0,
71
- AutoEvalColumn.dummy.name: "baseline",
72
- AutoEvalColumn.model_type.name: "",
73
- }
74
-
75
- human_baseline_row = {
76
- AutoEvalColumn.model.name: "<p>Human performance</p>",
77
- AutoEvalColumn.revision.name: "N/A",
78
- AutoEvalColumn.precision.name: None,
79
- AutoEvalColumn.average.name: 0,
80
- AutoEvalColumn.dummy.name: "human_baseline",
81
- AutoEvalColumn.model_type.name: "",
82
- }
83
-
84
  @dataclass
85
  class ModelDetails:
86
  name: str
 
3
 
4
  import pandas as pd
5
 
6
+ from src.display.about import Tasks
7
+
8
  def fields(raw_class):
9
  return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]
10
 
 
 
 
 
 
 
 
 
 
 
 
 
11
  # These classes are for user facing column names,
12
  # to avoid having to change them all around the code
13
  # when a modif is needed
 
20
  never_hidden: bool = False
21
  dummy: bool = False
22
 
23
+ ## Leaderboard columns
24
  auto_eval_column_dict = []
25
  # Init
26
  auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
 
45
  # We use make dataclass to dynamically fill the scores from Tasks
46
  AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
47
 
48
+ ## For the queue columns in the submission tab
49
  @dataclass(frozen=True)
50
  class EvalQueueColumn: # Queue column
51
  model = ColumnContent("model", "markdown", True)
 
55
  weight_type = ColumnContent("weight_type", "str", "Original")
56
  status = ColumnContent("status", "str", True)
57
 
58
+ ## All the model information that we might need
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
59
  @dataclass
60
  class ModelDetails:
61
  name: str
src/envs.py CHANGED
@@ -3,9 +3,9 @@ import os
3
  from huggingface_hub import HfApi
4
 
5
  # clone / pull the lmeh eval data
6
- H4_TOKEN = os.environ.get("H4_TOKEN", None)
7
 
8
- OWNER = "clefourrier"
9
  REPO_ID = f"{OWNER}/leaderboard"
10
  QUEUE_REPO = f"{OWNER}/requests"
11
  RESULTS_REPO = f"{OWNER}/results"
@@ -16,4 +16,4 @@ CACHE_PATH=os.getenv("HF_HOME", ".")
16
  EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")
17
  EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")
18
 
19
- API = HfApi(token=H4_TOKEN)
 
3
  from huggingface_hub import HfApi
4
 
5
  # clone / pull the lmeh eval data
6
+ TOKEN = os.environ.get("TOKEN", None)
7
 
8
+ OWNER = "demo-leaderboard"
9
  REPO_ID = f"{OWNER}/leaderboard"
10
  QUEUE_REPO = f"{OWNER}/requests"
11
  RESULTS_REPO = f"{OWNER}/results"
 
16
  EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")
17
  EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")
18
 
19
+ API = HfApi(token=TOKEN)
src/tools/collections.py DELETED
@@ -1,83 +0,0 @@
1
- import os
2
-
3
- import pandas as pd
4
- from huggingface_hub import add_collection_item, delete_collection_item, get_collection, update_collection_item
5
- from huggingface_hub.utils._errors import HfHubHTTPError
6
- from pandas import DataFrame
7
-
8
- from src.display.utils import AutoEvalColumn, ModelType
9
- from src.envs import H4_TOKEN, PATH_TO_COLLECTION
10
-
11
- # Specific intervals for the collections
12
- intervals = {
13
- "1B": pd.Interval(0, 1.5, closed="right"),
14
- "3B": pd.Interval(2.5, 3.5, closed="neither"),
15
- "7B": pd.Interval(6, 8, closed="neither"),
16
- "13B": pd.Interval(10, 14, closed="neither"),
17
- "30B": pd.Interval(25, 35, closed="neither"),
18
- "65B": pd.Interval(60, 70, closed="neither"),
19
- }
20
-
21
-
22
- def update_collections(df: DataFrame):
23
- """This function updates the Open LLM Leaderboard model collection with the latest best models for
24
- each size category and type.
25
- """
26
- collection = get_collection(collection_slug=PATH_TO_COLLECTION, token=H4_TOKEN)
27
- params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
28
-
29
- cur_best_models = []
30
-
31
- ix = 0
32
- for type in ModelType:
33
- if type.value.name == "":
34
- continue
35
- for size in intervals:
36
- # We filter the df to gather the relevant models
37
- type_emoji = [t[0] for t in type.value.symbol]
38
- filtered_df = df[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
39
-
40
- numeric_interval = pd.IntervalIndex([intervals[size]])
41
- mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
42
- filtered_df = filtered_df.loc[mask]
43
-
44
- best_models = list(
45
- filtered_df.sort_values(AutoEvalColumn.average.name, ascending=False)[AutoEvalColumn.dummy.name]
46
- )
47
- print(type.value.symbol, size, best_models[:10])
48
-
49
- # We add them one by one to the leaderboard
50
- for model in best_models:
51
- ix += 1
52
- cur_len_collection = len(collection.items)
53
- try:
54
- collection = add_collection_item(
55
- PATH_TO_COLLECTION,
56
- item_id=model,
57
- item_type="model",
58
- exists_ok=True,
59
- note=f"Best {type.to_str(' ')} model of around {size} on the leaderboard today!",
60
- token=H4_TOKEN,
61
- )
62
- if (
63
- len(collection.items) > cur_len_collection
64
- ): # we added an item - we make sure its position is correct
65
- item_object_id = collection.items[-1].item_object_id
66
- update_collection_item(
67
- collection_slug=PATH_TO_COLLECTION, item_object_id=item_object_id, position=ix
68
- )
69
- cur_len_collection = len(collection.items)
70
- cur_best_models.append(model)
71
- break
72
- except HfHubHTTPError:
73
- continue
74
-
75
- collection = get_collection(PATH_TO_COLLECTION, token=H4_TOKEN)
76
- for item in collection.items:
77
- if item.item_id not in cur_best_models:
78
- try:
79
- delete_collection_item(
80
- collection_slug=PATH_TO_COLLECTION, item_object_id=item.item_object_id, token=H4_TOKEN
81
- )
82
- except HfHubHTTPError:
83
- continue
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
src/tools/model_backlinks.py DELETED
@@ -1,1309 +0,0 @@
1
- models = [
2
- "uni-tianyan/Uni-TianYan",
3
- "fangloveskari/ORCA_LLaMA_70B_QLoRA",
4
- "garage-bAInd/Platypus2-70B-instruct",
5
- "upstage/Llama-2-70b-instruct-v2",
6
- "fangloveskari/Platypus_QLoRA_LLaMA_70b",
7
- "yeontaek/llama-2-70B-ensemble-v5",
8
- "TheBloke/Genz-70b-GPTQ",
9
- "TheBloke/Platypus2-70B-Instruct-GPTQ",
10
- "psmathur/model_007",
11
- "yeontaek/llama-2-70B-ensemble-v4",
12
- "psmathur/orca_mini_v3_70b",
13
- "ehartford/Samantha-1.11-70b",
14
- "MayaPH/GodziLLa2-70B",
15
- "psmathur/model_007_v2",
16
- "chargoddard/MelangeA-70b",
17
- "ehartford/Samantha-1.1-70b",
18
- "psmathur/model_009",
19
- "upstage/Llama-2-70b-instruct",
20
- "yeontaek/llama-2-70B-ensemble-v7",
21
- "yeontaek/llama-2-70B-ensemble-v6",
22
- "chargoddard/MelangeB-70b",
23
- "yeontaek/llama-2-70B-ensemble-v3",
24
- "chargoddard/MelangeC-70b",
25
- "garage-bAInd/Camel-Platypus2-70B",
26
- "yeontaek/llama-2-70B-ensemble-v2",
27
- "garage-bAInd/Camel-Platypus2-70B",
28
- "migtissera/Synthia-70B-v1.2",
29
- "v2ray/LLaMA-2-Wizard-70B-QLoRA",
30
- "quantumaikr/llama-2-70b-fb16-orca-chat-10k",
31
- "v2ray/LLaMA-2-Wizard-70B-QLoRA",
32
- "stabilityai/StableBeluga2",
33
- "quantumaikr/llama-2-70b-fb16-guanaco-1k",
34
- "garage-bAInd/Camel-Platypus2-70B",
35
- "migtissera/Synthia-70B-v1.1",
36
- "migtissera/Synthia-70B",
37
- "psmathur/model_101",
38
- "augtoma/qCammel70",
39
- "augtoma/qCammel-70",
40
- "augtoma/qCammel-70v1",
41
- "augtoma/qCammel-70x",
42
- "augtoma/qCammel-70-x",
43
- "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
44
- "dfurman/llama-2-70b-dolphin-peft",
45
- "jondurbin/airoboros-l2-70b-2.1",
46
- "TheBloke/llama-2-70b-Guanaco-QLoRA-fp16",
47
- "quantumaikr/QuantumLM-llama2-70B-Korean-LoRA",
48
- "quantumaikr/quantumairk-llama-2-70B-instruct",
49
- "psmathur/model_420",
50
- "psmathur/model_51",
51
- "garage-bAInd/Camel-Platypus2-70B",
52
- "TheBloke/Airoboros-L2-70B-2.1-GPTQ",
53
- "OpenAssistant/llama2-70b-oasst-sft-v10",
54
- "garage-bAInd/Platypus2-70B",
55
- "liuxiang886/llama2-70B-qlora-gpt4",
56
- "upstage/llama-65b-instruct",
57
- "quantumaikr/llama-2-70b-fb16-korean",
58
- "NousResearch/Nous-Hermes-Llama2-70b",
59
- "v2ray/LLaMA-2-Jannie-70B-QLoRA",
60
- "jondurbin/airoboros-l2-70b-gpt4-m2.0",
61
- "jondurbin/airoboros-l2-70b-gpt4-m2.0",
62
- "OpenAssistant/llama2-70b-oasst-sft-v10",
63
- "yeontaek/llama-2-70B-ensemble-v8",
64
- "jondurbin/airoboros-l2-70b-gpt4-2.0",
65
- "jarradh/llama2_70b_chat_uncensored",
66
- "WizardLM/WizardMath-70B-V1.0",
67
- "jordiclive/Llama-2-70b-oasst-1-200",
68
- "WizardLM/WizardMath-70B-V1.0",
69
- "jondurbin/airoboros-l2-70b-gpt4-2.0",
70
- "OpenLemur/lemur-70b-chat-v1",
71
- "tiiuae/falcon-180B",
72
- "tiiuae/falcon-180B",
73
- "stabilityai/StableBeluga1-Delta",
74
- "psmathur/model_42_70b",
75
- "psmathur/test_42_70b",
76
- "TheBloke/fiction.live-Kimiko-V2-70B-fp16",
77
- "tiiuae/falcon-180B",
78
- "WizardLM/WizardMath-70B-V1.0",
79
- "tiiuae/falcon-180B-chat",
80
- "jondurbin/airoboros-l2-70b-gpt4-2.0",
81
- "ehartford/samantha-1.1-llama-33b",
82
- "ajibawa-2023/scarlett-33b",
83
- "ddobokki/Llama-2-70b-orca-200k",
84
- "TheBloke/gpt4-alpaca-lora_mlp-65B-HF",
85
- "tiiuae/falcon-180B-chat",
86
- "tiiuae/falcon-180B-chat",
87
- "tiiuae/falcon-180B",
88
- "TheBloke/Lemur-70B-Chat-v1-GPTQ",
89
- "NousResearch/Nous-Puffin-70B",
90
- "WizardLM/WizardLM-70B-V1.0",
91
- "WizardLM/WizardMath-70B-V1.0",
92
- "meta-llama/Llama-2-70b-hf",
93
- "TheBloke/Llama-2-70B-fp16",
94
- "Weyaxi/llama-2-alpacagpt4-1000step",
95
- "WizardLM/WizardLM-70B-V1.0",
96
- "simsim314/WizardLM-70B-V1.0-HF",
97
- "simsim314/WizardLM-70B-V1.0-HF",
98
- "WizardLM/WizardLM-70B-V1.0",
99
- "openbmb/UltraLM-65b",
100
- "psmathur/model_420_preview",
101
- "WizardLM/WizardLM-70B-V1.0",
102
- "simsim314/WizardLM-70B-V1.0-HF",
103
- "OpenBuddy/openbuddy-llama2-70b-v10.1-bf16",
104
- "upstage/llama-30b-instruct-2048",
105
- "jondurbin/airoboros-65b-gpt4-1.2",
106
- "TheBloke/guanaco-65B-HF",
107
- "jondurbin/airoboros-65b-gpt4-1.3",
108
- "meta-llama/Llama-2-70b-chat-hf",
109
- "ValiantLabs/ShiningValiant",
110
- "Faradaylab/Aria-70B",
111
- "lilloukas/GPlatty-30B",
112
- "TheBloke/VicUnlocked-alpaca-65B-QLoRA-fp16",
113
- "jondurbin/airoboros-65b-gpt4-1.4-peft",
114
- "jondurbin/airoboros-65b-gpt4-1.4",
115
- "jondurbin/airoboros-65b-gpt4-2.0",
116
- "TheBloke/WizardLM-70B-V1.0-GPTQ",
117
- "TheBloke/WizardLM-70B-V1.0-GPTQ",
118
- "ariellee/SuperPlatty-30B",
119
- "jondurbin/airoboros-65b-gpt4-1.4",
120
- "jondurbin/airoboros-65b-gpt4-2.0",
121
- "yeontaek/llama-2-70b-IA3-guanaco",
122
- "CalderaAI/30B-Lazarus",
123
- "Aspik101/trurl-2-13b-pl-instruct_unload",
124
- "ehartford/WizardLM-33B-V1.0-Uncensored",
125
- "ehartford/WizardLM-33B-V1.0-Uncensored",
126
- "OpenBuddy/openbuddy-llama-65b-v8-bf16",
127
- "Aspik101/llama-30b-instruct-2048-PL-lora",
128
- "h2oai/h2ogpt-research-oasst1-llama-65b",
129
- "Aspik101/llama-30b-instruct-2048-PL-lora",
130
- "CalderaAI/30B-Epsilon",
131
- "Aspik101/llama-30b-2048-instruct-PL-lora_unload",
132
- "jondurbin/airoboros-65b-gpt4-m2.0",
133
- "jondurbin/airoboros-65b-gpt4-m2.0",
134
- "Aeala/Alpaca-elina-65b",
135
- "TheBloke/robin-65b-v2-fp16",
136
- "TheBloke/gpt4-alpaca-lora-30b-HF",
137
- "TheBloke/Llama-2-70B-chat-GPTQ",
138
- "upstage/llama-30b-instruct",
139
- "OpenLemur/lemur-70b-v1",
140
- "lmsys/vicuna-33b-v1.3",
141
- "ausboss/llama-30b-supercot",
142
- "ai-business/Luban-13B",
143
- "Henk717/airochronos-33B",
144
- "lmsys/vicuna-33b-v1.3",
145
- "Henk717/airochronos-33B",
146
- "bavest/fin-llama-33b-merged",
147
- "jondurbin/airoboros-33b-gpt4-1.4",
148
- "YeungNLP/firefly-llama-30b",
149
- "Aspik101/30B-Lazarus-instruct-PL-lora_unload",
150
- "uukuguy/speechless-llama2-luban-orca-platypus-13b",
151
- "xxyyy123/test_merge_p_ov1_w0.66_w0.5_n1",
152
- "jondurbin/airoboros-33b-gpt4-1.2",
153
- "TheBloke/alpaca-lora-65B-HF",
154
- "bofenghuang/vigogne-33b-instruct",
155
- "yeontaek/llama-2-13B-ensemble-v5",
156
- "garage-bAInd/Platypus-30B",
157
- "Open-Orca/OpenOrca-Platypus2-13B",
158
- "kajdun/viwaai-30b_v4",
159
- "lilloukas/Platypus-30B",
160
- "Open-Orca/OpenOrca-Platypus2-13B",
161
- "Henk717/chronoboros-33B",
162
- "jondurbin/airoboros-33b-2.1",
163
- "HiTZ/alpaca-lora-65b-en-pt-es-ca",
164
- "quantumaikr/QuantumLM-70B-hf",
165
- "uukuguy/speechless-llama2-13b",
166
- "uukuguy/speechless-llama2-hermes-orca-platypus-13b",
167
- "openaccess-ai-collective/manticore-30b-chat-pyg-alpha",
168
- "LLMs/WizardLM-30B-V1.0",
169
- "TheBloke/WizardLM-30B-fp16",
170
- "openaccess-ai-collective/hippogriff-30b-chat",
171
- "concedo/Vicuzard-30B-Uncensored",
172
- "TFLai/OpenOrca-Platypus2-13B-QLoRA-0.80-epoch",
173
- "huggingface/llama-65b",
174
- "huggyllama/llama-65b",
175
- "gaodrew/gaodrew-llama-30b-instruct-2048-Open-Platypus-100steps",
176
- "uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b",
177
- "Sao10K/Mythical-Destroyer-V2-L2-13B",
178
- "camel-ai/CAMEL-33B-Combined-Data",
179
- "dsvv-cair/alpaca-cleaned-llama-30b-bf16",
180
- "MetaIX/GPT4-X-Alpasta-30b",
181
- "garage-bAInd/Stable-Platypus2-13B",
182
- "TFLai/Luban-Platypus2-13B-QLora-0.80-epoch",
183
- "TheBloke/OpenOrca-Platypus2-13B-GPTQ",
184
- "IkariDev/Athena-tmp",
185
- "OpenBuddyEA/openbuddy-llama-30b-v7.1-bf16",
186
- "OpenBuddyEA/openbuddy-llama-30b-v7.1-bf16",
187
- "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
188
- "psmathur/model_007_13b_v2",
189
- "Aspik101/Vicuzard-30B-Uncensored-instruct-PL-lora_unload",
190
- "jondurbin/airoboros-33b-gpt4-m2.0",
191
- "Sao10K/Mythical-Destroyer-L2-13B",
192
- "TheBloke/Wizard-Vicuna-30B-Uncensored-fp16",
193
- "ehartford/Wizard-Vicuna-30B-Uncensored",
194
- "TFLai/Nova-13B",
195
- "TheBloke/robin-33B-v2-fp16",
196
- "totally-not-an-llm/PuddleJumper-13b",
197
- "Aeala/VicUnlocked-alpaca-30b",
198
- "Yhyu13/oasst-rlhf-2-llama-30b-7k-steps-hf",
199
- "jondurbin/airoboros-33b-gpt4",
200
- "jondurbin/airoboros-33b-gpt4-m2.0",
201
- "tiiuae/falcon-40b-instruct",
202
- "psmathur/orca_mini_v3_13b",
203
- "Aeala/GPT4-x-AlpacaDente-30b",
204
- "MayaPH/GodziLLa-30B",
205
- "jondurbin/airoboros-33b-gpt4-m2.0",
206
- "TFLai/SpeechlessV1-Nova-13B",
207
- "yeontaek/llama-2-13B-ensemble-v4",
208
- "ajibawa-2023/carl-33b",
209
- "jondurbin/airoboros-33b-gpt4-2.0",
210
- "TFLai/Stable-Platypus2-13B-QLoRA-0.80-epoch",
211
- "jondurbin/airoboros-33b-gpt4-1.3",
212
- "TehVenom/oasst-sft-6-llama-33b-xor-MERGED-16bit",
213
- "TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch",
214
- "jondurbin/airoboros-33b-gpt4-2.0",
215
- "chargoddard/Chronorctypus-Limarobormes-13b",
216
- "jondurbin/airoboros-33b-gpt4-1.3",
217
- "Open-Orca/OpenOrca-Platypus2-13B",
218
- "FelixChao/vicuna-33b-coder",
219
- "FelixChao/vicuna-33b-coder",
220
- "Gryphe/MythoMix-L2-13b",
221
- "Aeala/Enterredaas-33b",
222
- "yeontaek/llama-2-13B-ensemble-v1",
223
- "TFLai/OpenOrcaPlatypus2-Platypus2-13B-QLora-0.80-epoch",
224
- "TFLai/Ensemble5-Platypus2-13B-QLora-0.80-epoch",
225
- "yeontaek/llama-2-13B-ensemble-v3",
226
- "TFLai/MythoMix-Platypus2-13B-QLoRA-0.80-epoch",
227
- "yihan6324/llama2-13b-instructmining-40k-sharegpt",
228
- "timdettmers/guanaco-33b-merged",
229
- "TFLai/EnsembleV5-Nova-13B",
230
- "circulus/Llama-2-13b-orca-v1",
231
- "Undi95/ReMM-SLERP-L2-13B",
232
- "Gryphe/MythoMax-L2-13b",
233
- "stabilityai/StableBeluga-13B",
234
- "circulus/Llama-2-13b-orca-v1",
235
- "ehartford/WizardLM-30B-Uncensored",
236
- "The-Face-Of-Goonery/huginnv1.2",
237
- "TheBloke/OpenOrcaxOpenChat-Preview2-13B-GPTQ",
238
- "Sao10K/Stheno-L2-13B",
239
- "bofenghuang/vigogne-2-13b-instruct",
240
- "The-Face-Of-Goonery/Huginn-13b-FP16",
241
- "grimpep/L2-MythoMax22b-instruct-Falseblock",
242
- "TFLai/Nous-Hermes-Platypus2-13B-QLoRA-0.80-epoch",
243
- "yeontaek/Platypus2xOpenOrca-13B-IA3-v4",
244
- "yeontaek/Platypus2xOpenOrca-13B-IA3",
245
- "yeontaek/Platypus2xOpenOrca-13B-IA3-ensemble",
246
- "Open-Orca/LlongOrca-13B-16k",
247
- "Sao10K/Stheno-Inverted-L2-13B",
248
- "garage-bAInd/Camel-Platypus2-13B",
249
- "digitous/Alpacino30b",
250
- "NousResearch/Nous-Hermes-Llama2-13b",
251
- "yeontaek/Platypus2xOpenOrca-13B-IA3-v3",
252
- "TFLai/MythicalDestroyerV2-Platypus2-13B-QLora-0.80-epoch",
253
- "TheBloke/VicUnlocked-30B-LoRA-HF",
254
- "Undi95/Nous-Hermes-13B-Code",
255
- "The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16",
256
- "NousResearch/Nous-Hermes-Llama2-13b",
257
- "Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b",
258
- "TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ",
259
- "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
260
- "Austism/chronos-hermes-13b-v2",
261
- "yeontaek/Platypus2xOpenOrca-13B-IA3-v2.1",
262
- "yeontaek/Platypus2xOpenOrca-13B-IA3-v2",
263
- "Gryphe/MythoLogic-L2-13b",
264
- "augtoma/qCammel-13",
265
- "YeungNLP/firefly-llama2-13b-v1.2",
266
- "Aspik101/StableBeluga-13B-instruct-PL-lora_unload",
267
- "andreaskoepf/llama2-13b-megacode2_min100",
268
- "rombodawg/LosslessMegaCoder-llama2-13b-mini",
269
- "yulan-team/YuLan-Chat-2-13b-fp16",
270
- "elinas/chronos-33b",
271
- "YeungNLP/firefly-llama2-13b",
272
- "Sao10K/Medusa-13b",
273
- "OptimalScale/robin-65b-v2-delta",
274
- "minlik/chinese-alpaca-33b-merged",
275
- "OpenAssistant/llama2-13b-megacode2-oasst",
276
- "TheBloke/OpenAssistant-SFT-7-Llama-30B-HF",
277
- "Undi95/UndiMix-v1-13b",
278
- "ehartford/Samantha-1.11-13b",
279
- "beaugogh/Llama2-13b-sharegpt4",
280
- "Aeala/GPT4-x-AlpacaDente2-30b",
281
- "luffycodes/nash-vicuna-13b-v1dot5-ep2-w-rag-w-simple",
282
- "WizardLM/WizardLM-13B-V1.1",
283
- "uukuguy/speechless-orca-platypus-coig-lite-2k-0.6e-13b",
284
- "huggyllama/llama-30b",
285
- "Undi95/ReMM-L2-13B-PIPPA",
286
- "Undi95/ReMM-L2-13B",
287
- "gaodrew/gaodrew-gorgonzola-13b",
288
- "lmsys/vicuna-13b-v1.5",
289
- "yeontaek/Platypus2xOpenOrca-13B-LoRa",
290
- "Yhyu13/llama-30B-hf-openassitant",
291
- "huggingface/llama-30b",
292
- "lmsys/vicuna-13b-v1.5",
293
- "TFLai/Athena-Platypus2-13B-QLora-0.80-epoch",
294
- "TheBloke/dromedary-65b-lora-HF",
295
- "yeontaek/llama-2-13b-Beluga-QLoRA",
296
- "The-Face-Of-Goonery/Huginn-13b-V4",
297
- "The-Face-Of-Goonery/Huginn-13b-v4.5",
298
- "The-Face-Of-Goonery/Huginn-v3-13b",
299
- "tiiuae/falcon-40b",
300
- "WhoTookMyAmogusNickname/NewHope_HF_not_official",
301
- "gaodrew/OpenOrca-Platypus2-13B-thera-1250",
302
- "SLAM-group/NewHope",
303
- "garage-bAInd/Platypus2-13B",
304
- "migtissera/Synthia-13B",
305
- "elinas/chronos-13b-v2",
306
- "mosaicml/mpt-30b-chat",
307
- "CHIH-HUNG/llama-2-13b-OpenOrca_5w",
308
- "uukuguy/speechless-hermes-coig-lite-13b",
309
- "TheBloke/tulu-30B-fp16",
310
- "uukuguy/speechless-hermes-coig-lite-13b",
311
- "xDAN-AI/xDAN_13b_l2_lora",
312
- "lmsys/vicuna-13b-v1.5-16k",
313
- "openchat/openchat_v3.1",
314
- "CHIH-HUNG/llama-2-13b-dolphin_5w",
315
- "Aspik101/vicuna-13b-v1.5-PL-lora_unload",
316
- "Undi95/MLewd-L2-13B",
317
- "ehartford/minotaur-llama2-13b-qlora",
318
- "kajdun/iubaris-13b-v3",
319
- "TFLai/Limarp-Platypus2-13B-QLoRA-0.80-epoch",
320
- "openchat/openchat_v3.1",
321
- "uukuguy/speechless-orca-platypus-coig-lite-4k-0.6e-13b",
322
- "ziqingyang/chinese-alpaca-2-13b",
323
- "TFLai/Airboros2.1-Platypus2-13B-QLora-0.80-epoch",
324
- "yeontaek/llama-2-13b-Guanaco-QLoRA",
325
- "lmsys/vicuna-13b-v1.5-16k",
326
- "ehartford/based-30b",
327
- "kingbri/airolima-chronos-grad-l2-13B",
328
- "openchat/openchat_v3.2",
329
- "uukuguy/speechless-orca-platypus-coig-lite-4k-0.5e-13b",
330
- "yeontaek/Platypus2-13B-LoRa",
331
- "kingbri/chronolima-airo-grad-l2-13B",
332
- "openchat/openchat_v3.2",
333
- "TFLai/PuddleJumper-Platypus2-13B-QLoRA-0.80-epoch",
334
- "shareAI/llama2-13b-Chinese-chat",
335
- "ehartford/WizardLM-1.0-Uncensored-Llama2-13b",
336
- "Aspik101/Redmond-Puffin-13B-instruct-PL-lora_unload",
337
- "yeontaek/llama-2-13B-ensemble-v6",
338
- "WizardLM/WizardLM-13B-V1.2",
339
- "TheBloke/WizardLM-13B-V1.1-GPTQ",
340
- "bhenrym14/airophin-13b-pntk-16k-fp16",
341
- "ehartford/WizardLM-1.0-Uncensored-Llama2-13b",
342
- "Mikael110/llama-2-13b-guanaco-fp16",
343
- "yeontaek/airoboros-2.1-llama-2-13B-QLoRa",
344
- "CalderaAI/13B-Legerdemain-L2",
345
- "grimpep/llama2-22b-wizard_vicuna",
346
- "grimpep/llama2-22B-GPLATTY",
347
- "bhenrym14/airophin-13b-pntk-16k-fp16",
348
- "yeontaek/llama-2-13b-QLoRA",
349
- "OpenAssistant/llama2-13b-orca-8k-3319",
350
- "TheBloke/WizardLM-13B-V1-1-SuperHOT-8K-fp16",
351
- "duliadotio/dulia-13b-8k-alpha",
352
- "Undi95/LewdEngine",
353
- "OpenBuddy/openbuddy-llama2-13b-v8.1-fp16",
354
- "CHIH-HUNG/llama-2-13b-open_orca_20w",
355
- "bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16",
356
- "FlagAlpha/Llama2-Chinese-13b-Chat",
357
- "LLMs/WizardLM-13B-V1.0",
358
- "chansung/gpt4-alpaca-lora-13b-decapoda-1024",
359
- "TheBloke/wizardLM-13B-1.0-fp16",
360
- "digitous/13B-Chimera",
361
- "yeontaek/Platypus2xOpenOrcaxGuanaco-13B-LoRa",
362
- "jondurbin/airoboros-l2-13b-2.1",
363
- "Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b",
364
- "TheBloke/UltraLM-13B-fp16",
365
- "openaccess-ai-collective/minotaur-13b-fixed",
366
- "NousResearch/Redmond-Puffin-13B",
367
- "KoboldAI/LLaMA2-13B-Holomax",
368
- "Lajonbot/WizardLM-13B-V1.2-PL-lora_unload",
369
- "yeontaek/Platypus2-13B-LoRa-v2",
370
- "TheBloke/airoboros-13B-HF",
371
- "jondurbin/airoboros-13b",
372
- "jjaaaww/posi_13b",
373
- "CoolWP/llama-2-13b-guanaco-fp16",
374
- "yeontaek/Platypus2-13B-QLoRa",
375
- "h2oai/h2ogpt-research-oig-oasst1-512-30b",
376
- "dfurman/llama-2-13b-guanaco-peft",
377
- "NousResearch/Redmond-Puffin-13B",
378
- "pe-nlp/llama-2-13b-platypus-vicuna-wizard",
379
- "CHIH-HUNG/llama-2-13b-dolphin_20w",
380
- "NousResearch/Nous-Hermes-13b",
381
- "NobodyExistsOnTheInternet/GiftedConvo13bLoraNoEconsE4",
382
- "ehartford/Wizard-Vicuna-13B-Uncensored",
383
- "TheBloke/Wizard-Vicuna-13B-Uncensored-HF",
384
- "openchat/openchat_v3.2_super",
385
- "bhenrym14/airophin-v2-13b-PI-8k-fp16",
386
- "openaccess-ai-collective/manticore-13b",
387
- "The-Face-Of-Goonery/Huginn-22b-Prototype",
388
- "jphme/Llama-2-13b-chat-german",
389
- "grimpep/llama2-28B-Airo03",
390
- "TheBloke/Kimiko-v2-13B-fp16",
391
- "FPHam/Free_Sydney_13b_HF",
392
- "lmsys/vicuna-13b-v1.3",
393
- "FelixChao/llama2-13b-math1.1",
394
- "CalderaAI/13B-BlueMethod",
395
- "meta-llama/Llama-2-13b-chat-hf",
396
- "deepse/CodeUp-Llama-2-13b-chat-hf",
397
- "WizardLM/WizardMath-13B-V1.0",
398
- "WizardLM/WizardMath-13B-V1.0",
399
- "HyperbeeAI/Tulpar-7b-v0",
400
- "xxyyy123/test_qkvo_adptor",
401
- "xxyyy123/mc_data_30k_from_platpus_orca_7b_10k_v1_lora_qkvo_rank14_v2",
402
- "openchat/openchat_v2_w",
403
- "FelixChao/llama2-13b-math1.1",
404
- "psmathur/orca_mini_v3_7b",
405
- "TehVenom/Metharme-13b-Merged",
406
- "xxyyy123/10k_v1_lora_qkvo_rank14_v3",
407
- "OpenAssistant/llama2-13b-orca-v2-8k-3166",
408
- "openaccess-ai-collective/wizard-mega-13b",
409
- "jondurbin/airoboros-13b-gpt4-1.4",
410
- "jondurbin/airoboros-13b-gpt4-1.4-fp16",
411
- "Monero/Manticore-13b-Chat-Pyg-Guanaco",
412
- "FelixChao/llama2-13b-math1.2",
413
- "chargoddard/platypus-2-22b-relora",
414
- "FelixChao/llama2-13b-math1.2",
415
- "Gryphe/MythoBoros-13b",
416
- "CalderaAI/13B-Ouroboros",
417
- "OpenAssistant/llama2-13b-orca-v2-8k-3166",
418
- "heegyu/LIMA2-13b-hf",
419
- "digitous/13B-HyperMantis",
420
- "Gryphe/MythoLogic-13b",
421
- "TheBloke/Airoboros-L2-13B-2.1-GPTQ",
422
- "chargoddard/platypus2-22b-relora",
423
- "openchat/openchat_v2",
424
- "yeontaek/Platypus2-13B-IA3",
425
- "stabilityai/StableBeluga-7B",
426
- "circulus/Llama-2-7b-orca-v1",
427
- "budecosystem/genz-13b-v2",
428
- "TheBloke/gpt4-x-vicuna-13B-HF",
429
- "NobodyExistsOnTheInternet/GiftedConvo13bLoraNoEcons",
430
- "zarakiquemparte/zarafusionex-1.1-l2-7b",
431
- "Lajonbot/tableBeluga-7B-instruct-pl-lora_unload",
432
- "jondurbin/airoboros-13b-gpt4",
433
- "gaodrew/gaodrew-gorgonzola-13b",
434
- "jondurbin/airoboros-13b-gpt4-1.1",
435
- "TheBloke/gpt4-alpaca-lora-13B-HF",
436
- "zarakiquemparte/zarablendex-vq-l2-7b",
437
- "openaccess-ai-collective/manticore-13b-chat-pyg",
438
- "Lajonbot/Llama-2-13b-hf-instruct-pl-lora_unload",
439
- "NobodyExistsOnTheInternet/PuffedLIMA13bQLORA",
440
- "xxyyy123/10k_v1_lora_qkvo_rank28_v2",
441
- "jondurbin/airoboros-l2-13b-gpt4-1.4.1",
442
- "dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16",
443
- "NobodyExistsOnTheInternet/PuffedConvo13bLoraE4",
444
- "yihan6324/llama2-7b-instructmining-40k-sharegpt",
445
- "CHIH-HUNG/llama-2-13b-Open_Platypus_and_ccp_2.6w",
446
- "Aeala/GPT4-x-Alpasta-13b",
447
- "psmathur/orca_mini_v2_13b",
448
- "YeungNLP/firefly-llama-13b",
449
- "psmathur/orca_mini_v2_13b",
450
- "zarakiquemparte/zarafusionix-l2-7b",
451
- "yihan6324/llama2-7b-instructmining-60k-sharegpt",
452
- "yihan6324/llama-2-7b-instructmining-60k-sharegpt",
453
- "layoric/llama-2-13b-code-alpaca",
454
- "bofenghuang/vigogne-13b-instruct",
455
- "Lajonbot/vicuna-13b-v1.3-PL-lora_unload",
456
- "lvkaokao/llama2-7b-hf-chat-lora-v3",
457
- "ehartford/dolphin-llama-13b",
458
- "YeungNLP/firefly-llama-13b-v1.2",
459
- "TheBloke/Kimiko-13B-fp16",
460
- "kevinpro/Vicuna-13B-CoT",
461
- "eachadea/vicuna-13b-1.1",
462
- "pillowtalks-ai/delta13b",
463
- "TheBloke/vicuna-13B-1.1-HF",
464
- "TheBloke/Vicuna-13B-CoT-fp16",
465
- "lmsys/vicuna-13b-delta-v1.1",
466
- "lmsys/vicuna-13b-v1.1",
467
- "xxyyy123/20k_v1_lora_qkvo_rank14_v2",
468
- "TheBloke/guanaco-13B-HF",
469
- "TheBloke/vicuna-13b-v1.3.0-GPTQ",
470
- "edor/Stable-Platypus2-mini-7B",
471
- "totally-not-an-llm/EverythingLM-13b-V2-16k",
472
- "zarakiquemparte/zaraxe-l2-7b",
473
- "beaugogh/Llama2-7b-openorca-mc-v2",
474
- "TheBloke/Nous-Hermes-13B-SuperHOT-8K-fp16",
475
- "quantumaikr/QuantumLM",
476
- "jondurbin/airoboros-13b-gpt4-1.2",
477
- "TheBloke/robin-13B-v2-fp16",
478
- "TFLai/llama-2-13b-4bit-alpaca-gpt4",
479
- "yihan6324/llama2-7b-instructmining-orca-40k",
480
- "dvruette/oasst-llama-13b-2-epochs",
481
- "Open-Orca/LlongOrca-7B-16k",
482
- "Aspik101/Nous-Hermes-13b-pl-lora_unload",
483
- "ehartford/Samantha-1.11-CodeLlama-34b",
484
- "nkpz/llama2-22b-chat-wizard-uncensored",
485
- "bofenghuang/vigogne-13b-chat",
486
- "beaugogh/Llama2-7b-openorca-mc-v1",
487
- "OptimalScale/robin-13b-v2-delta",
488
- "pe-nlp/llama-2-13b-vicuna-wizard",
489
- "chargoddard/llama2-22b",
490
- "gywy/llama2-13b-chinese-v1",
491
- "frank098/Wizard-Vicuna-13B-juniper",
492
- "IGeniusDev/llama13B-quant8-testv1-openorca-customdataset",
493
- "CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w-gate_up_down_proj",
494
- "eachadea/vicuna-13b",
495
- "yihan6324/llama2-7b-instructmining-orca-90k",
496
- "chargoddard/llama2-22b-blocktriangular",
497
- "luffycodes/mcq-vicuna-13b-v1.5",
498
- "Yhyu13/chimera-inst-chat-13b-hf",
499
- "luffycodes/mcq-vicuna-13b-v1.5",
500
- "chargoddard/ypotryll-22b-epoch2-qlora",
501
- "totally-not-an-llm/EverythingLM-13b-16k",
502
- "luffycodes/mcq-hal-vicuna-13b-v1.5",
503
- "openaccess-ai-collective/minotaur-13b",
504
- "IGeniusDev/llama13B-quant8-testv1-openorca-customdataset",
505
- "chargoddard/llama2-22b-blocktriangular",
506
- "TFLai/Platypus2-13B-QLoRA-0.80-epoch",
507
- "meta-llama/Llama-2-13b-hf",
508
- "CHIH-HUNG/llama-2-13b-huangyt_FINETUNE2_3w-gate_up_down_proj",
509
- "luffycodes/mcq-hal-vicuna-13b-v1.5",
510
- "TheBloke/Llama-2-13B-fp16",
511
- "TaylorAI/Flash-Llama-13B",
512
- "shareAI/bimoGPT-llama2-13b",
513
- "wahaha1987/llama_13b_sharegpt94k_fastchat",
514
- "openchat/openchat_8192",
515
- "CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w-q_k_v_o_proj",
516
- "dvruette/llama-13b-pretrained-sft-do2",
517
- "CHIH-HUNG/llama-2-13b-alpaca-test",
518
- "OpenBuddy/openbuddy-llama2-13b-v11.1-bf16",
519
- "CHIH-HUNG/llama-2-13b-FINETUNE2_TEST_2.2w",
520
- "project-baize/baize-v2-13b",
521
- "jondurbin/airoboros-l2-13b-gpt4-m2.0",
522
- "yeontaek/Platypus2xOpenOrca-13B-LoRa-v2",
523
- "CHIH-HUNG/llama-2-13b-huangyt_FINETUNE2_3w",
524
- "xzuyn/Alpacino-SuperCOT-13B",
525
- "jondurbin/airoboros-l2-13b-gpt4-2.0",
526
- "aiplanet/effi-13b",
527
- "clibrain/Llama-2-13b-ft-instruct-es",
528
- "CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w",
529
- "bofenghuang/vigogne-2-7b-instruct",
530
- "CHIH-HUNG/llama-2-13b-huangyt_FINETUNE2_3w-q_k_v_o_proj",
531
- "bofenghuang/vigogne-2-7b-chat",
532
- "aiplanet/effi-13b",
533
- "haonan-li/bactrian-x-llama-13b-merged",
534
- "beaugogh/Llama2-7b-sharegpt4",
535
- "HWERI/Llama2-7b-sharegpt4",
536
- "jondurbin/airoboros-13b-gpt4-1.3",
537
- "jondurbin/airoboros-c34b-2.1",
538
- "junelee/wizard-vicuna-13b",
539
- "TheBloke/wizard-vicuna-13B-HF",
540
- "Open-Orca/OpenOrca-Preview1-13B",
541
- "TheBloke/h2ogpt-oasst1-512-30B-HF",
542
- "TheBloke/Llama-2-13B-GPTQ",
543
- "camel-ai/CAMEL-13B-Combined-Data",
544
- "lmsys/vicuna-7b-v1.5",
545
- "lmsys/vicuna-7b-v1.5-16k",
546
- "lmsys/vicuna-7b-v1.5",
547
- "ausboss/llama-13b-supercot",
548
- "TheBloke/tulu-13B-fp16",
549
- "NousResearch/Nous-Hermes-llama-2-7b",
550
- "jlevin/guanaco-13b-llama-2",
551
- "lmsys/vicuna-7b-v1.5-16k",
552
- "dvruette/llama-13b-pretrained",
553
- "nkpz/llama2-22b-daydreamer-v3",
554
- "dvruette/llama-13b-pretrained-dropout",
555
- "jondurbin/airoboros-l2-13b-2.1",
556
- "LLMs/Stable-Vicuna-13B",
557
- "64bits/LexPodLM-13B",
558
- "lizhuang144/llama_mirror_13b_v1.0",
559
- "TheBloke/stable-vicuna-13B-HF",
560
- "zarakiquemparte/zaraxls-l2-7b",
561
- "TheBloke/Llama-2-13B-GPTQ",
562
- "Kiddyz/testlm-3",
563
- "migtissera/Synthia-7B",
564
- "zarakiquemparte/zarablend-l2-7b",
565
- "mosaicml/mpt-30b-instruct",
566
- "PocketDoc/Dans-PileOfSets-Mk1-llama-13b-merged",
567
- "vonjack/Qwen-LLaMAfied-HFTok-7B-Chat",
568
- "l3utterfly/llama2-7b-layla",
569
- "Lajonbot/vicuna-7b-v1.5-PL-lora_unload",
570
- "heegyu/LIMA-13b-hf",
571
- "frank098/WizardLM_13B_juniper",
572
- "ashercn97/manatee-7b",
573
- "chavinlo/gpt4-x-alpaca",
574
- "PocketDoc/Dans-PersonalityEngine-13b",
575
- "ehartford/WizardLM-1.0-Uncensored-CodeLlama-34b",
576
- "digitous/Alpacino13b",
577
- "edor/Hermes-Platypus2-mini-7B",
578
- "lvkaokao/llama2-7b-hf-chat-lora-v2",
579
- "Kiddyz/testlm-1-1",
580
- "Kiddyz/testlm",
581
- "Kiddyz/testlm-1",
582
- "Kiddyz/testlm2",
583
- "radm/Philosophy-Platypus2-13b",
584
- "aiplanet/effi-13b",
585
- "Harshvir/Llama-2-7B-physics",
586
- "YeungNLP/firefly-ziya-13b",
587
- "LinkSoul/Chinese-Llama-2-7b",
588
- "PeanutJar/LLaMa-2-PeanutButter_v10-7B",
589
- "OpenBuddy/openbuddy-llama2-13b-v11-bf16",
590
- "StudentLLM/Alpagasus-2-13B-QLoRA-pipeline",
591
- "meta-llama/Llama-2-13b-hf",
592
- "WizardLM/WizardCoder-Python-34B-V1.0",
593
- "dvruette/llama-13b-pretrained-sft-epoch-1",
594
- "camel-ai/CAMEL-13B-Role-Playing-Data",
595
- "ziqingyang/chinese-llama-2-13b",
596
- "rombodawg/LosslessMegaCoder-llama2-7b-mini",
597
- "TheBloke/koala-13B-HF",
598
- "lmsys/vicuna-7b-delta-v1.1",
599
- "eachadea/vicuna-7b-1.1",
600
- "Ejafa/vicuna_7B_vanilla_1.1",
601
- "lvkaokao/llama2-7b-hf-chat-lora",
602
- "OpenBuddy/openbuddy-atom-13b-v9-bf16",
603
- "Norquinal/llama-2-7b-claude-chat-rp",
604
- "Danielbrdz/Barcenas-7b",
605
- "heegyu/WizardVicuna2-13b-hf",
606
- "meta-llama/Llama-2-7b-chat-hf",
607
- "PeanutJar/LLaMa-2-PeanutButter_v14-7B",
608
- "PeanutJar/LLaMa-2-PeanutButter_v4-7B",
609
- "davzoku/cria-llama2-7b-v1.3",
610
- "OpenBuddy/openbuddy-atom-13b-v9-bf16",
611
- "lvkaokao/llama2-7b-hf-instruction-lora",
612
- "Tap-M/Luna-AI-Llama2-Uncensored",
613
- "ehartford/Samantha-1.11-7b",
614
- "WizardLM/WizardCoder-Python-34B-V1.0",
615
- "TheBloke/Manticore-13B-Chat-Pyg-Guanaco-SuperHOT-8K-GPTQ",
616
- "Mikael110/llama-2-7b-guanaco-fp16",
617
- "garage-bAInd/Platypus2-7B",
618
- "PeanutJar/LLaMa-2-PeanutButter_v18_B-7B",
619
- "mosaicml/mpt-30b",
620
- "garage-bAInd/Platypus2-7B",
621
- "huggingface/llama-13b",
622
- "dvruette/oasst-llama-13b-1000-steps",
623
- "jordiclive/gpt4all-alpaca-oa-codealpaca-lora-13b",
624
- "huggyllama/llama-13b",
625
- "Voicelab/trurl-2-7b",
626
- "TFLai/llama-13b-4bit-alpaca",
627
- "gywy/llama2-13b-chinese-v2",
628
- "lmsys/longchat-13b-16k",
629
- "Aspik101/trurl-2-7b-pl-instruct_unload",
630
- "WizardLM/WizardMath-7B-V1.0",
631
- "Norquinal/llama-2-7b-claude-chat",
632
- "TheTravellingEngineer/llama2-7b-chat-hf-dpo",
633
- "HuggingFaceH4/starchat-beta",
634
- "joehuangx/spatial-vicuna-7b-v1.5-LoRA",
635
- "conceptofmind/LLongMA-2-13b-16k",
636
- "tianyil1/denas-llama2",
637
- "lmsys/vicuna-7b-v1.3",
638
- "conceptofmind/LLongMA-2-13b-16k",
639
- "openchat/opencoderplus",
640
- "ajibawa-2023/scarlett-7b",
641
- "dhmeltzer/llama-7b-SFT_eli5_wiki65k_1024_r_64_alpha_16_merged",
642
- "psyche/kollama2-7b-v2",
643
- "heegyu/LIMA2-7b-hf",
644
- "dhmeltzer/llama-7b-SFT-qlora-eli5-wiki_DPO_ds_RM_top_2_1024_r_64_alpha_16",
645
- "abhishek/llama2guanacotest",
646
- "jondurbin/airoboros-l2-7b-2.1",
647
- "llama-anon/instruct-13b",
648
- "FelixChao/vicuna-7B-physics",
649
- "Aspik101/Llama-2-7b-hf-instruct-pl-lora_unload",
650
- "shibing624/chinese-alpaca-plus-13b-hf",
651
- "davzoku/cria-llama2-7b-v1.3_peft",
652
- "quantumaikr/llama-2-7b-hf-guanaco-1k",
653
- "togethercomputer/Llama-2-7B-32K-Instruct",
654
- "sia-ai/llama-2-7b-1-percent-open-orca-1000-steps-v0",
655
- "TheTravellingEngineer/llama2-7b-hf-guanaco",
656
- "Lajonbot/Llama-2-7b-chat-hf-instruct-pl-lora_unload",
657
- "jondurbin/airoboros-l2-7b-gpt4-1.4.1",
658
- "wahaha1987/llama_7b_sharegpt94k_fastchat",
659
- "FelixChao/vicuna-7B-chemical",
660
- "TinyPixel/llama2-7b-oa",
661
- "chaoyi-wu/MedLLaMA_13B",
662
- "edor/Platypus2-mini-7B",
663
- "RoversX/llama-2-7b-hf-small-shards-Samantha-V1-SFT",
664
- "venkycs/llama-v2-7b-32kC-Security",
665
- "psyche/kollama2-7b",
666
- "Fredithefish/Guanaco-7B-Uncensored",
667
- "TheTravellingEngineer/llama2-7b-chat-hf-guanaco",
668
- "ehartford/WizardLM-13B-Uncensored",
669
- "PocketDoc/Dans-CreepingSenseOfDoom",
670
- "wenge-research/yayi-7b-llama2",
671
- "georgesung/llama2_7b_chat_uncensored",
672
- "TinyPixel/llama2-7b-instruct",
673
- "quantumaikr/QuantumLM-7B",
674
- "xzuyn/MedicWizard-7B",
675
- "wenge-research/yayi-7b-llama2",
676
- "TinyPixel/lima-test",
677
- "elyza/ELYZA-japanese-Llama-2-7b-instruct",
678
- "lgaalves/llama-2-7b-hf_open-platypus",
679
- "ziqingyang/chinese-alpaca-2-7b",
680
- "TehVenom/Pygmalion-Vicuna-1.1-7b",
681
- "meta-llama/Llama-2-7b-hf",
682
- "bongchoi/test-llama2-7b",
683
- "TaylorAI/Flash-Llama-7B",
684
- "TheTravellingEngineer/llama2-7b-chat-hf-v2",
685
- "TheTravellingEngineer/llama2-7b-chat-hf-v4",
686
- "kashif/stack-llama-2",
687
- "PeanutJar/LLaMa-2-PeanutButter_v18_A-7B",
688
- "ToolBench/ToolLLaMA-7b-LoRA",
689
- "Monero/WizardLM-13b-OpenAssistant-Uncensored",
690
- "TheTravellingEngineer/llama2-7b-chat-hf-v2",
691
- "TheTravellingEngineer/llama2-7b-chat-hf-v4",
692
- "mrm8488/llama-2-coder-7b",
693
- "elyza/ELYZA-japanese-Llama-2-7b-fast-instruct",
694
- "clibrain/Llama-2-7b-ft-instruct-es",
695
- "medalpaca/medalpaca-7b",
696
- "TheBloke/tulu-7B-fp16",
697
- "OpenBuddy/openbuddy-openllama-13b-v7-fp16",
698
- "TaylorAI/FLAN-Llama-7B-2_Llama2-7B-Flash_868_full_model",
699
- "Aspik101/vicuna-7b-v1.3-instruct-pl-lora_unload",
700
- "jondurbin/airoboros-l2-7b-gpt4-2.0",
701
- "dhmeltzer/llama-7b-SFT_ds_eli5_1024_r_64_alpha_16_merged",
702
- "GOAT-AI/GOAT-7B-Community",
703
- "AtomEchoAI/AtomGPT_56k",
704
- "julianweng/Llama-2-7b-chat-orcah",
705
- "TehVenom/Pygmalion-13b-Merged",
706
- "jondurbin/airoboros-7b-gpt4-1.1",
707
- "dhmeltzer/llama-7b-SFT_ds_wiki65k_1024_r_64_alpha_16_merged",
708
- "bofenghuang/vigogne-7b-chat",
709
- "lmsys/longchat-7b-v1.5-32k",
710
- "jondurbin/airoboros-l2-7b-gpt4-m2.0",
711
- "synapsoft/Llama-2-7b-chat-hf-flan2022-1.2M",
712
- "jondurbin/airoboros-7b-gpt4-1.4",
713
- "Charlie911/vicuna-7b-v1.5-lora-mctaco",
714
- "yihan6324/instructmining-platypus-15k",
715
- "meta-llama/Llama-2-7b-hf",
716
- "TheTravellingEngineer/llama2-7b-chat-hf-v3",
717
- "quantumaikr/KoreanLM-hf",
718
- "openthaigpt/openthaigpt-1.0.0-alpha-7b-chat-ckpt-hf",
719
- "TheBloke/Llama-2-7B-GPTQ",
720
- "TheBloke/Llama-2-7B-GPTQ",
721
- "LLMs/AlpacaGPT4-7B-elina",
722
- "ehartford/Wizard-Vicuna-7B-Uncensored",
723
- "TheBloke/Wizard-Vicuna-7B-Uncensored-HF",
724
- "TheTravellingEngineer/llama2-7b-chat-hf-v3",
725
- "golaxy/gowizardlm",
726
- "ehartford/dolphin-llama2-7b",
727
- "CHIH-HUNG/llama-2-7b-dolphin_10w-test",
728
- "mncai/chatdoctor",
729
- "psyche/kollama2-7b-v3",
730
- "jondurbin/airoboros-7b-gpt4",
731
- "jondurbin/airoboros-7b",
732
- "TheBloke/airoboros-7b-gpt4-fp16",
733
- "mosaicml/mpt-7b-8k-chat",
734
- "elyza/ELYZA-japanese-Llama-2-7b",
735
- "bofenghuang/vigogne-7b-instruct",
736
- "jxhong/CAlign-alpaca-7b",
737
- "golaxy/goims",
738
- "jondurbin/airoboros-7b-gpt4-1.2",
739
- "jphme/orca_mini_v2_ger_7b",
740
- "psmathur/orca_mini_v2_7b",
741
- "notstoic/PygmalionCoT-7b",
742
- "golaxy/gogpt2-13b",
743
- "golaxy/gogpt2-13b-chat",
744
- "togethercomputer/LLaMA-2-7B-32K",
745
- "TheBloke/wizardLM-7B-HF",
746
- "keyfan/vicuna-chinese-replication-v1.1",
747
- "golaxy/gogpt2-7b",
748
- "aiplanet/effi-7b",
749
- "arver/llama7b-qlora",
750
- "titan087/OpenLlama13B-Guanaco",
751
- "chavinlo/alpaca-native",
752
- "project-baize/baize-healthcare-lora-7B",
753
- "AlpinDale/pygmalion-instruct",
754
- "openlm-research/open_llama_13b",
755
- "jondurbin/airoboros-7b-gpt4-1.3",
756
- "elyza/ELYZA-japanese-Llama-2-7b-fast",
757
- "jondurbin/airoboros-gpt-3.5-turbo-100k-7b",
758
- "uukuguy/speechless-codellama-orca-13b",
759
- "bigcode/starcoderplus",
760
- "TheBloke/guanaco-7B-HF",
761
- "Neko-Institute-of-Science/metharme-7b",
762
- "TigerResearch/tigerbot-7b-base",
763
- "golaxy/gogpt-7b",
764
- "togethercomputer/LLaMA-2-7B-32K",
765
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766
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767
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768
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769
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770
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771
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772
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773
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774
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775
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776
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777
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778
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779
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780
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781
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782
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783
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784
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785
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786
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787
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788
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789
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790
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791
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792
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793
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794
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795
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796
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797
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798
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799
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800
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801
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802
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803
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804
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805
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806
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807
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808
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809
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810
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811
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812
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813
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814
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815
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816
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817
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818
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819
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820
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821
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822
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823
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824
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825
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826
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827
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828
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829
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830
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831
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832
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833
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834
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835
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836
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837
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838
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839
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840
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841
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842
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843
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844
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845
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846
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847
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848
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849
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850
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851
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852
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853
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854
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855
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856
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857
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858
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859
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860
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861
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862
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863
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864
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865
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866
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867
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868
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869
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870
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871
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872
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873
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874
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875
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876
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877
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878
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879
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880
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881
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882
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883
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884
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885
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886
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887
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888
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889
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890
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891
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892
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893
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894
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895
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896
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897
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898
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899
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900
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901
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902
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903
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904
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905
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906
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907
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908
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909
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910
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911
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912
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913
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914
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915
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916
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917
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918
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919
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920
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921
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922
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923
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924
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925
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926
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927
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928
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929
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930
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931
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932
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933
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934
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935
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936
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937
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938
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939
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940
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941
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942
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943
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944
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945
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946
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947
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948
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949
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950
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951
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952
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953
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954
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955
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956
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957
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958
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959
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960
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961
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962
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963
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964
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965
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966
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967
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968
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969
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970
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971
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972
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973
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974
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975
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976
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977
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978
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979
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980
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981
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982
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983
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984
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985
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986
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987
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988
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989
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990
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991
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992
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993
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994
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995
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996
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997
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998
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999
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1000
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1001
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1002
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1003
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1004
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1005
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1006
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1007
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1008
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1009
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1010
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1011
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1012
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1013
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1014
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1015
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1016
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1017
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1018
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1019
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1020
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1021
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1022
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1023
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1024
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1025
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1026
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1027
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1028
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1029
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1030
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1031
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1032
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1033
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1034
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1035
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1036
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1037
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1038
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1039
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1040
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1041
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1042
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1043
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1044
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1045
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1046
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1047
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1048
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1049
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1050
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1051
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1052
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1053
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1054
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1055
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1056
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1057
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1058
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1059
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1060
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1061
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1062
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1063
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1064
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1065
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1066
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1067
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1068
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1069
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1070
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1071
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1072
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1073
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1074
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1075
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1076
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1077
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1078
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1079
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1080
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1081
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1082
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1083
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1084
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1085
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1086
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1087
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1088
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1089
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1090
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1091
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1092
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1093
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1094
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1095
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1096
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1097
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1098
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1099
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1100
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1101
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1102
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1103
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1104
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1105
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1106
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1107
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1108
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1109
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1110
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1111
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1112
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1113
- "FabbriSimo01/Bloom_1b_Quantized",
1114
- "MBZUAI/LaMini-GPT-774M",
1115
- "Locutusque/gpt2-large-conversational",
1116
- "Devio/test-3b",
1117
- "stabilityai/stablelm-tuned-alpha-3b",
1118
- "PygmalionAI/pygmalion-1.3b",
1119
- "KoboldAI/fairseq-dense-355M",
1120
- "Rachneet/gpt2-xl-alpaca",
1121
- "gpt2-large",
1122
- "Mikivis/gpt2-large-lora-sft",
1123
- "stabilityai/stablelm-base-alpha-3b",
1124
- "gpt2-medium",
1125
- "Kunhao/pile-7b",
1126
- "aisquared/dlite-v1-774m",
1127
- "aisquared/dlite-v2-355m",
1128
- "YeungNLP/firefly-bloom-2b6-v2",
1129
- "KnutJaegersberg/gpt-2-xl-EvolInstruct",
1130
- "KnutJaegersberg/galactica-orca-wizardlm-1.3b",
1131
- "cerebras/Cerebras-GPT-1.3B",
1132
- "FabbriSimo01/Cerebras_1.3b_Quantized",
1133
- "facebook/xglm-1.7B",
1134
- "EleutherAI/pythia-410m-deduped",
1135
- "TheBloke/GPlatty-30B-SuperHOT-8K-fp16",
1136
- "DataLinguistic/DataLinguistic-34B-V1.0",
1137
- "Corianas/Quokka_1.3b",
1138
- "TheTravellingEngineer/bloom-560m-RLHF-v2",
1139
- "Corianas/1.3b",
1140
- "RWKV/rwkv-4-430m-pile",
1141
- "porkorbeef/Llama-2-13b-sf",
1142
- "xhyi/PT_GPTNEO350_ATG",
1143
- "TheBloke/Wizard-Vicuna-13B-Uncensored-GPTQ",
1144
- "bigscience/bloomz-560m",
1145
- "TheBloke/medalpaca-13B-GPTQ-4bit",
1146
- "TheBloke/Vicuna-33B-1-3-SuperHOT-8K-fp16",
1147
- "aisquared/dlite-v1-355m",
1148
- "uukuguy/speechless-codellama-orca-airoboros-13b-0.10e",
1149
- "yhyhy3/med-orca-instruct-33b",
1150
- "TheBloke/Wizard-Vicuna-30B-Superhot-8K-fp16",
1151
- "TheTravellingEngineer/bloom-1b1-RLHF",
1152
- "MBZUAI/lamini-cerebras-1.3b",
1153
- "IDEA-CCNL/Ziya-LLaMA-13B-Pretrain-v1",
1154
- "TheBloke/WizardLM-7B-uncensored-GPTQ",
1155
- "TheBloke/EverythingLM-13B-16K-GPTQ",
1156
- "quantumaikr/open_llama_7b_hf",
1157
- "TheBloke/chronos-wizardlm-uc-scot-st-13B-GPTQ",
1158
- "TheBloke/WizardLM-30B-Uncensored-GPTQ",
1159
- "IDEA-CCNL/Ziya-LLaMA-13B-v1",
1160
- "Phind/Phind-CodeLlama-34B-v1",
1161
- "robowaifudev/megatron-gpt2-345m",
1162
- "MayaPH/GodziLLa-30B-instruct",
1163
- "TheBloke/CAMEL-33B-Combined-Data-SuperHOT-8K-fp16",
1164
- "uukuguy/speechless-codellama-orca-platypus-13b-0.10e",
1165
- "doas/test2",
1166
- "BreadAi/PM_modelV2",
1167
- "bigcode/santacoder",
1168
- "TheBloke/wizard-vicuna-13B-GPTQ",
1169
- "porkorbeef/Llama-2-13b",
1170
- "TehVenom/DiffMerge-DollyGPT-Pygmalion",
1171
- "PygmalionAI/pygmalion-350m",
1172
- "TheBloke/orca_mini_v3_7B-GPTQ",
1173
- "TheBloke/WizardLM-Uncensored-SuperCOT-StoryTelling-30B-GPTQ",
1174
- "TheBloke/WizardLM-30B-GPTQ",
1175
- "bigscience/bloom-560m",
1176
- "TFLai/gpt2-turkish-uncased",
1177
- "TheBloke/guanaco-33B-GPTQ",
1178
- "TheBloke/openchat_v2_openorca_preview-GPTQ",
1179
- "porkorbeef/Llama-2-13b-public",
1180
- "TheBloke/LongChat-13B-GPTQ",
1181
- "yhyhy3/med-orca-instruct-33b",
1182
- "TheBloke/airoboros-33B-gpt4-1-4-SuperHOT-8K-fp16",
1183
- "TheBloke/Chinese-Alpaca-33B-SuperHOT-8K-fp16",
1184
- "MayaPH/FinOPT-Franklin",
1185
- "TheBloke/WizardLM-33B-V1.0-Uncensored-GPTQ",
1186
- "TheBloke/Project-Baize-v2-13B-GPTQ",
1187
- "malhajar/Platypus2-70B-instruct-4bit-gptq",
1188
- "KoboldAI/OPT-350M-Erebus",
1189
- "rishiraj/bloom-560m-guanaco",
1190
- "Panchovix/WizardLM-33B-V1.0-Uncensored-SuperHOT-8k",
1191
- "doas/test5",
1192
- "vicgalle/alpaca-7b",
1193
- "beomi/KoAlpaca-Polyglot-5.8B",
1194
- "Phind/Phind-CodeLlama-34B-Python-v1",
1195
- "timdettmers/guanaco-65b-merged",
1196
- "TheBloke/wizard-mega-13B-GPTQ",
1197
- "MayaPH/GodziLLa-30B-plus",
1198
- "TheBloke/Platypus-30B-SuperHOT-8K-fp16",
1199
- "facebook/opt-350m",
1200
- "KoboldAI/OPT-350M-Nerys-v2",
1201
- "TheBloke/robin-33B-v2-GPTQ",
1202
- "jaspercatapang/Echidna-30B",
1203
- "TheBloke/llama-30b-supercot-SuperHOT-8K-fp16",
1204
- "marcchew/test1",
1205
- "Harshvir/LaMini-Neo-1.3B-Mental-Health_lora",
1206
- "golaxy/gogpt-560m",
1207
- "TheBloke/orca_mini_13B-GPTQ",
1208
- "Panchovix/airoboros-33b-gpt4-1.2-SuperHOT-8k",
1209
- "Aspik101/tulu-7b-instruct-pl-lora_unload",
1210
- "Phind/Phind-CodeLlama-34B-v2",
1211
- "BreadAi/MusePy-1-2",
1212
- "cerebras/Cerebras-GPT-590M",
1213
- "microsoft/CodeGPT-small-py",
1214
- "victor123/WizardLM-13B-1.0",
1215
- "OptimalScale/robin-65b-v2-delta",
1216
- "voidful/changpt-bart",
1217
- "FabbriSimo01/GPT_Large_Quantized",
1218
- "MayaPH/FinOPT-Lincoln",
1219
- "KoboldAI/fairseq-dense-125M",
1220
- "SebastianSchramm/Cerebras-GPT-111M-instruction",
1221
- "TheTravellingEngineer/bloom-560m-RLHF",
1222
- "breadlicker45/dough-instruct-base-001",
1223
- "WizardLM/WizardLM-30B-V1.0",
1224
- "WizardLM/WizardLM-30B-V1.0",
1225
- "WizardLM/WizardLM-30B-V1.0",
1226
- "TaylorAI/Flash-Llama-30M-20001",
1227
- "porkorbeef/Llama-2-13b-12_153950",
1228
- "huggingtweets/bladeecity-jerma985",
1229
- "KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct",
1230
- "bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16",
1231
- "microsoft/DialoGPT-small",
1232
- "Corianas/590m",
1233
- "facebook/xglm-564M",
1234
- "EleutherAI/gpt-neo-125m",
1235
- "EleutherAI/pythia-160m-deduped",
1236
- "klosax/pythia-160m-deduped-step92k-193bt",
1237
- "MBZUAI/lamini-neo-125m",
1238
- "bigcode/tiny_starcoder_py",
1239
- "concedo/OPT-19M-ChatSalad",
1240
- "anton-l/gpt-j-tiny-random",
1241
- "grantprice/Cerebras-GPT-590M-finetuned-DND",
1242
- "deepnight-research/zsc-text",
1243
- "WangZeJun/bloom-820m-chat",
1244
- "cerebras/Cerebras-GPT-256M",
1245
- "ai-forever/rugpt3large_based_on_gpt2",
1246
- "alibidaran/medical_transcription_generator",
1247
- "Deci/DeciCoder-1b",
1248
- "microsoft/DialoGPT-medium",
1249
- "ogimgio/gpt-neo-125m-neurallinguisticpioneers",
1250
- "open-llm-leaderboard/bloom-560m-4bit-alpaca-auto-eval-adapter-applied",
1251
- "BreadAi/gpt-YA-1-1_160M",
1252
- "microsoft/DialoGPT-large",
1253
- "facebook/opt-125m",
1254
- "huggingtweets/jerma985",
1255
- "Locutusque/gpt2-conversational-or-qa",
1256
- "concedo/Pythia-70M-ChatSalad",
1257
- "roneneldan/TinyStories-1M",
1258
- "BreadAi/DiscordPy",
1259
- "bigcode/gpt_bigcode-santacoder",
1260
- "Tincando/fiction_story_generator",
1261
- "klosax/pythia-70m-deduped-step44k-92bt",
1262
- "Quake24/easyTermsSummerizer",
1263
- "BreadAi/gpt-YA-1-1_70M",
1264
- "EleutherAI/pythia-160m",
1265
- "euclaise/gpt-neox-122m-minipile-digits",
1266
- "MBZUAI/lamini-cerebras-590m",
1267
- "nicholasKluge/Aira-124M",
1268
- "MayaPH/FinOPT-Washington",
1269
- "cyberagent/open-calm-large",
1270
- "BreadAi/StoryPy",
1271
- "EleutherAI/pythia-70m",
1272
- "BreadAi/gpt-Youtube",
1273
- "roneneldan/TinyStories-33M",
1274
- "EleutherAI/pythia-70m-deduped",
1275
- "lgaalves/gpt2_guanaco-dolly-platypus",
1276
- "Corianas/Quokka_590m",
1277
- "lgaalves/gpt2_platypus-dolly-guanaco",
1278
- "cyberagent/open-calm-7b",
1279
- "RWKV/rwkv-4-169m-pile",
1280
- "gpt2",
1281
- "roneneldan/TinyStories-28M",
1282
- "lgaalves/gpt2_open-platypus",
1283
- "gpt2",
1284
- "SaylorTwift/gpt2_test",
1285
- "roneneldan/TinyStories-3M",
1286
- "nthngdy/pythia-owt2-70m-50k",
1287
- "Corianas/256_5epoch",
1288
- "roneneldan/TinyStories-8M",
1289
- "lgaalves/gpt2-dolly",
1290
- "nthngdy/pythia-owt2-70m-100k",
1291
- "aisquared/dlite-v2-124m",
1292
- "mncai/SGPT-1.3B-insurance-epoch10",
1293
- "huggingtweets/gladosystem",
1294
- "abhiramtirumala/DialoGPT-sarcastic-medium",
1295
- "MBZUAI/lamini-cerebras-256m",
1296
- "cerebras/Cerebras-GPT-111M",
1297
- "uberkie/metharme-1.3b-finetuned",
1298
- "MBZUAI/lamini-cerebras-111m",
1299
- "psyche/kogpt",
1300
- "Corianas/Quokka_256m",
1301
- "vicgalle/gpt2-alpaca-gpt4",
1302
- "aisquared/dlite-v1-124m",
1303
- "Mikivis/xuanxuan",
1304
- "MBZUAI/LaMini-GPT-124M",
1305
- "vicgalle/gpt2-alpaca",
1306
- "huashiyiqike/testmodel",
1307
- "Corianas/111m",
1308
- "baseline",
1309
- ]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
src/tools/plots.py DELETED
@@ -1,154 +0,0 @@
1
- import pandas as pd
2
- import numpy as np
3
- import plotly.express as px
4
- from plotly.graph_objs import Figure
5
-
6
- from src.leaderboard.filter_models import FLAGGED_MODELS
7
- from src.display.utils import human_baseline_row as HUMAN_BASELINE, AutoEvalColumn, Tasks, Task, BENCHMARK_COLS
8
- from src.leaderboard.read_evals import EvalResult
9
-
10
-
11
-
12
- def create_scores_df(raw_data: list[EvalResult]) -> pd.DataFrame:
13
- """
14
- Generates a DataFrame containing the maximum scores until each date.
15
-
16
- :param results_df: A DataFrame containing result information including metric scores and dates.
17
- :return: A new DataFrame containing the maximum scores until each date for every metric.
18
- """
19
- # Step 1: Ensure 'date' is in datetime format and sort the DataFrame by it
20
- results_df = pd.DataFrame(raw_data)
21
- #results_df["date"] = pd.to_datetime(results_df["date"], format="mixed", utc=True)
22
- results_df.sort_values(by="date", inplace=True)
23
-
24
- # Step 2: Initialize the scores dictionary
25
- scores = {k: [] for k in BENCHMARK_COLS + [AutoEvalColumn.average.name]}
26
-
27
- # Step 3: Iterate over the rows of the DataFrame and update the scores dictionary
28
- for task in [t.value for t in Tasks] + [Task("Average", "avg", AutoEvalColumn.average.name)]:
29
- current_max = 0
30
- last_date = ""
31
- column = task.col_name
32
- for _, row in results_df.iterrows():
33
- current_model = row["full_model"]
34
- if current_model in FLAGGED_MODELS:
35
- continue
36
-
37
- current_date = row["date"]
38
- if task.benchmark == "Average":
39
- current_score = np.mean(list(row["results"].values()))
40
- else:
41
- current_score = row["results"][task.benchmark]
42
-
43
- if current_score > current_max:
44
- if current_date == last_date and len(scores[column]) > 0:
45
- scores[column][-1] = {"model": current_model, "date": current_date, "score": current_score}
46
- else:
47
- scores[column].append({"model": current_model, "date": current_date, "score": current_score})
48
- current_max = current_score
49
- last_date = current_date
50
-
51
- # Step 4: Return all dictionaries as DataFrames
52
- return {k: pd.DataFrame(v) for k, v in scores.items()}
53
-
54
-
55
- def create_plot_df(scores_df: dict[str: pd.DataFrame]) -> pd.DataFrame:
56
- """
57
- Transforms the scores DataFrame into a new format suitable for plotting.
58
-
59
- :param scores_df: A DataFrame containing metric scores and dates.
60
- :return: A new DataFrame reshaped for plotting purposes.
61
- """
62
- # Initialize the list to store DataFrames
63
- dfs = []
64
-
65
- # Iterate over the cols and create a new DataFrame for each column
66
- for col in BENCHMARK_COLS + [AutoEvalColumn.average.name]:
67
- d = scores_df[col].reset_index(drop=True)
68
- d["task"] = col
69
- dfs.append(d)
70
-
71
- # Concatenate all the created DataFrames
72
- concat_df = pd.concat(dfs, ignore_index=True)
73
-
74
- # Sort values by 'date'
75
- concat_df.sort_values(by="date", inplace=True)
76
- concat_df.reset_index(drop=True, inplace=True)
77
- return concat_df
78
-
79
-
80
- def create_metric_plot_obj(
81
- df: pd.DataFrame, metrics: list[str], title: str
82
- ) -> Figure:
83
- """
84
- Create a Plotly figure object with lines representing different metrics
85
- and horizontal dotted lines representing human baselines.
86
-
87
- :param df: The DataFrame containing the metric values, names, and dates.
88
- :param metrics: A list of strings representing the names of the metrics
89
- to be included in the plot.
90
- :param title: A string representing the title of the plot.
91
- :return: A Plotly figure object with lines representing metrics and
92
- horizontal dotted lines representing human baselines.
93
- """
94
-
95
- # Filter the DataFrame based on the specified metrics
96
- df = df[df["task"].isin(metrics)]
97
-
98
- # Filter the human baselines based on the specified metrics
99
- filtered_human_baselines = {k: v for k, v in HUMAN_BASELINE.items() if k in metrics}
100
-
101
- # Create a line figure using plotly express with specified markers and custom data
102
- fig = px.line(
103
- df,
104
- x="date",
105
- y="score",
106
- color="task",
107
- markers=True,
108
- custom_data=["task", "score", "model"],
109
- title=title,
110
- )
111
-
112
- # Update hovertemplate for better hover interaction experience
113
- fig.update_traces(
114
- hovertemplate="<br>".join(
115
- [
116
- "Model Name: %{customdata[2]}",
117
- "Metric Name: %{customdata[0]}",
118
- "Date: %{x}",
119
- "Metric Value: %{y}",
120
- ]
121
- )
122
- )
123
-
124
- # Update the range of the y-axis
125
- fig.update_layout(yaxis_range=[0, 100])
126
-
127
- # Create a dictionary to hold the color mapping for each metric
128
- metric_color_mapping = {}
129
-
130
- # Map each metric name to its color in the figure
131
- for trace in fig.data:
132
- metric_color_mapping[trace.name] = trace.line.color
133
-
134
- # Iterate over filtered human baselines and add horizontal lines to the figure
135
- for metric, value in filtered_human_baselines.items():
136
- color = metric_color_mapping.get(metric, "blue") # Retrieve color from mapping; default to blue if not found
137
- location = "top left" if metric == "HellaSwag" else "bottom left" # Set annotation position
138
- # Add horizontal line with matched color and positioned annotation
139
- fig.add_hline(
140
- y=value,
141
- line_dash="dot",
142
- annotation_text=f"{metric} human baseline",
143
- annotation_position=location,
144
- annotation_font_size=10,
145
- annotation_font_color=color,
146
- line_color=color,
147
- )
148
-
149
- return fig
150
-
151
-
152
- # Example Usage:
153
- # human_baselines dictionary is defined.
154
- # chart = create_metric_plot_obj(scores_df, ["ARC", "HellaSwag", "MMLU", "TruthfulQA"], human_baselines, "Graph Title")