Push model using huggingface_hub.
Browse files- .gitattributes +1 -0
- README.md +44 -0
- adapter_config.json +29 -0
- adapter_model.safetensors +3 -0
- config.json +77 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +34 -0
- tokenizer.json +3 -0
- tokenizer.model +3 -0
- tokenizer_config.json +2014 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,44 @@
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---
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+
license: apache-2.0
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+
library_name: transformers
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tags:
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- trl
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- ppo
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- transformers
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- reinforcement-learning
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---
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# TRL Model
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+
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
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guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
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+
## Usage
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To use this model for inference, first install the TRL library:
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```bash
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python -m pip install trl
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```
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You can then generate text as follows:
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```python
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from transformers import pipeline
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|
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generator = pipeline("text-generation", model="jvelja//tmp/tmpb73nk20r/jvelja/vllm-gemma2b-stringMatcher-newDataset_2")
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outputs = generator("Hello, my llama is cute")
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```
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|
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+
If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
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|
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+
```python
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+
from transformers import AutoTokenizer
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from trl import AutoModelForCausalLMWithValueHead
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|
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tokenizer = AutoTokenizer.from_pretrained("jvelja//tmp/tmpb73nk20r/jvelja/vllm-gemma2b-stringMatcher-newDataset_2")
|
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model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/tmpb73nk20r/jvelja/vllm-gemma2b-stringMatcher-newDataset_2")
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|
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+
inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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outputs = model(**inputs, labels=inputs["input_ids"])
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+
```
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adapter_config.json
ADDED
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{
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"alpha_pattern": {},
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+
"auto_mapping": null,
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+
"base_model_name_or_path": "unsloth/gemma-2-2b-it",
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+
"bias": "none",
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+
"fan_in_fan_out": false,
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+
"inference_mode": true,
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+
"init_lora_weights": true,
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+
"layer_replication": null,
|
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+
"layers_pattern": null,
|
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+
"layers_to_transform": null,
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+
"loftq_config": {},
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+
"lora_alpha": 16,
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+
"lora_dropout": 0.05,
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+
"megatron_config": null,
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+
"megatron_core": "megatron.core",
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+
"modules_to_save": null,
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+
"peft_type": "LORA",
|
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+
"r": 16,
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+
"rank_pattern": {},
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+
"revision": null,
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+
"target_modules": [
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"v_proj",
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+
"q_proj"
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+
],
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"task_type": "CAUSAL_LM",
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+
"use_dora": false,
|
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+
"use_rslora": false
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}
|
adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:489fd171065f8f13adc3b8692b7734417458b8ff86ab24f3b0671c5d7de89b07
|
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+
size 12793376
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config.json
ADDED
@@ -0,0 +1,77 @@
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{
|
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+
"accelerator_kwargs": {},
|
3 |
+
"adap_kl_ctrl": true,
|
4 |
+
"backward_batch_size": 64,
|
5 |
+
"batch_size": 64,
|
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+
"cliprange": 0.2,
|
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+
"cliprange_value": 0.2,
|
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+
"compare_steps": 1,
|
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+
"dataset_num_proc": null,
|
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+
"early_stopping": false,
|
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+
"exp_name": "stego_trainer",
|
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+
"forward_batch_size": null,
|
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"gamma": 1,
|
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+
"global_backward_batch_size": 64,
|
15 |
+
"global_batch_size": 64,
|
16 |
+
"gradient_accumulation_steps": 4,
|
17 |
+
"gradient_checkpointing": false,
|
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+
"horizon": 10000,
|
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+
"init_kl_coef": 0.05,
|
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+
"is_encoder_decoder": false,
|
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+
"is_peft_model": true,
|
22 |
+
"kl_penalty": "kl",
|
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+
"lam": 0.95,
|
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+
"learning_rate": 2e-05,
|
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+
"log_with": "wandb",
|
26 |
+
"max_grad_norm": null,
|
27 |
+
"mini_batch_size": 16,
|
28 |
+
"model_name": "unsloth/gemma-2-2b-it",
|
29 |
+
"optimize_cuda_cache": true,
|
30 |
+
"optimize_device_cache": false,
|
31 |
+
"ppo_epochs": 4,
|
32 |
+
"project_kwargs": {},
|
33 |
+
"push_to_hub_if_best_kwargs": {},
|
34 |
+
"query_dataset": "imdb",
|
35 |
+
"ratio_threshold": 10.0,
|
36 |
+
"remove_unused_columns": true,
|
37 |
+
"reward_model": "sentiment-analysis:lvwerra/distilbert-imdb",
|
38 |
+
"score_clip": null,
|
39 |
+
"seed": 0,
|
40 |
+
"steps": 20000,
|
41 |
+
"target": 12.0,
|
42 |
+
"target_kl": 1,
|
43 |
+
"task_name": null,
|
44 |
+
"tracker_kwargs": {
|
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+
"wandb": {
|
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+
"name": "cv_gemma-2-2b-it_to_distilbert-base-uncased_EBS64_Joan",
|
47 |
+
"notes": "Dataset: cv\n Same Prompt: \n Payload Prefixes: ['Movie Review: This movie was really amazing!', 'Movie Review: This movie was really terrible!']\n Payload Template: Movie Review: This movie was really {payload}!\n Separate Enc/Dec Data: True\n\n Encoder: gemma-2-2b-it (LR: 2e-05)\n Decoder: distilbert-base-uncased (LR: 1e-05)\n Train Loop: v2_dylan\n\n Effective Batch Sizes:\n - Encoder: 64\n - Decoder: 512\n\n Training Iterations:\n - Encoder updates: 100\n - Decoder updates: 400\n - Update Encoder First: False\n\n Temperatures:\n - Decoder Training: 1.0\n - Encoder Training: 1.0\n - Evaluation: 1.0\n\n Encoder Parameters:\n - KL Coefficient: 0.05\n - LoRA: True\n - Quantization: False\n - Output Length: {'min': 42, 'max': 51}\n\n Decoder Parameters:\n - New Classification Head: True\n - Use Probs Reward: False\n - Weight Decay: 0.01\n - Update Parameters: {'head': True, 'body': True}\n\n Training Configuration:\n - Update Encoder: True\n - Update Decoder: True\n - Paraphrase: False\n - Leak Password: False\n - WandB Logging: True\n - Eval Every N: 50\n - Number of Epochs: 100000\n\n Debug:\n - Override Dec Batch: False",
|
48 |
+
"tags": [
|
49 |
+
"cv",
|
50 |
+
"gemma-2-2b-it",
|
51 |
+
"distilbert-base-uncased",
|
52 |
+
"v2_dylan",
|
53 |
+
"enc_lr_2e-05",
|
54 |
+
"dec_lr_1e-05",
|
55 |
+
"enc_eff_bs_64",
|
56 |
+
"dec_eff_bs_512",
|
57 |
+
"enc_updates_100",
|
58 |
+
"dec_updates_400",
|
59 |
+
"LoRA",
|
60 |
+
"Full_Precision",
|
61 |
+
"same_prompt_ ",
|
62 |
+
"Separate_Enc_Dec_Data",
|
63 |
+
"Update_Enc",
|
64 |
+
"Update_Dec",
|
65 |
+
"No_Paraphrase",
|
66 |
+
"No_Leak",
|
67 |
+
"1-bit"
|
68 |
+
]
|
69 |
+
}
|
70 |
+
},
|
71 |
+
"tracker_project_name": "trl",
|
72 |
+
"use_score_norm": false,
|
73 |
+
"use_score_scaling": false,
|
74 |
+
"vf_coef": 0.1,
|
75 |
+
"whiten_rewards": false,
|
76 |
+
"world_size": 1
|
77 |
+
}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:bd640758d08a99c34be9defb8d28b35afb00760d8d1d40156e34095642c55178
|
3 |
+
size 10748
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special_tokens_map.json
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{
|
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"additional_special_tokens": [
|
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+
"<start_of_turn>",
|
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+
"<end_of_turn>"
|
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+
],
|
6 |
+
"bos_token": {
|
7 |
+
"content": "<bos>",
|
8 |
+
"lstrip": false,
|
9 |
+
"normalized": false,
|
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"rstrip": false,
|
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"single_word": false
|
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},
|
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"eos_token": {
|
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"content": "<eos>",
|
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+
"lstrip": false,
|
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+
"normalized": false,
|
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"rstrip": false,
|
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"single_word": false
|
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+
},
|
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+
"pad_token": {
|
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+
"content": "<pad>",
|
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+
"lstrip": false,
|
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"normalized": false,
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+
"rstrip": false,
|
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+
"single_word": false
|
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+
},
|
27 |
+
"unk_token": {
|
28 |
+
"content": "<unk>",
|
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+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
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+
"single_word": false
|
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+
}
|
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+
}
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tokenizer.json
ADDED
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1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3f289bc05132635a8bc7aca7aa21255efd5e18f3710f43e3cdb96bcd41be4922
|
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+
size 17525357
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tokenizer.model
ADDED
@@ -0,0 +1,3 @@
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1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
|
3 |
+
size 4241003
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tokenizer_config.json
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1 |
+
{
|
2 |
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"add_bos_token": true,
|
3 |
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"add_eos_token": false,
|
4 |
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"added_tokens_decoder": {
|
5 |
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6 |
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7 |
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8 |
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10 |
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11 |
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12 |
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16 |
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|
18 |
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|
19 |
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|
20 |
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21 |
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22 |
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23 |
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24 |
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25 |
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26 |
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27 |
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28 |
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29 |
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|
30 |
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31 |
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32 |
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33 |
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34 |
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35 |
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36 |
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37 |
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38 |
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39 |
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40 |
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41 |
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42 |
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43 |
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44 |
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45 |
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46 |
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48 |
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50 |
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52 |
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53 |
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54 |
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55 |
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56 |
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"lstrip": false,
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},
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"255990": {
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"content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
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"lstrip": false,
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1921 |
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},
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"255991": {
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"lstrip": false,
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1928 |
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1932 |
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},
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1934 |
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"lstrip": false,
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|
1939 |
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1940 |
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},
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"lstrip": false,
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1944 |
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1946 |
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1947 |
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1948 |
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},
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1949 |
+
"255994": {
|
1950 |
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"content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
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1951 |
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1952 |
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|
1953 |
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|
1954 |
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"single_word": false,
|
1955 |
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"special": false
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1956 |
+
},
|
1957 |
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"255995": {
|
1958 |
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"content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
|
1959 |
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"lstrip": false,
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1960 |
+
"normalized": false,
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1961 |
+
"rstrip": false,
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1962 |
+
"single_word": false,
|
1963 |
+
"special": false
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1964 |
+
},
|
1965 |
+
"255996": {
|
1966 |
+
"content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
|
1967 |
+
"lstrip": false,
|
1968 |
+
"normalized": false,
|
1969 |
+
"rstrip": false,
|
1970 |
+
"single_word": false,
|
1971 |
+
"special": false
|
1972 |
+
},
|
1973 |
+
"255997": {
|
1974 |
+
"content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
|
1975 |
+
"lstrip": false,
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1976 |
+
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+
"rstrip": false,
|
1978 |
+
"single_word": false,
|
1979 |
+
"special": false
|
1980 |
+
},
|
1981 |
+
"255998": {
|
1982 |
+
"content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
|
1983 |
+
"lstrip": false,
|
1984 |
+
"normalized": false,
|
1985 |
+
"rstrip": false,
|
1986 |
+
"single_word": false,
|
1987 |
+
"special": false
|
1988 |
+
},
|
1989 |
+
"255999": {
|
1990 |
+
"content": "<unused99>",
|
1991 |
+
"lstrip": false,
|
1992 |
+
"normalized": false,
|
1993 |
+
"rstrip": false,
|
1994 |
+
"single_word": false,
|
1995 |
+
"special": false
|
1996 |
+
}
|
1997 |
+
},
|
1998 |
+
"additional_special_tokens": [
|
1999 |
+
"<start_of_turn>",
|
2000 |
+
"<end_of_turn>"
|
2001 |
+
],
|
2002 |
+
"bos_token": "<bos>",
|
2003 |
+
"chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
|
2004 |
+
"clean_up_tokenization_spaces": false,
|
2005 |
+
"eos_token": "<eos>",
|
2006 |
+
"model_max_length": 1000000000000000019884624838656,
|
2007 |
+
"pad_token": "<pad>",
|
2008 |
+
"padding_side": "left",
|
2009 |
+
"sp_model_kwargs": {},
|
2010 |
+
"spaces_between_special_tokens": false,
|
2011 |
+
"tokenizer_class": "GemmaTokenizer",
|
2012 |
+
"unk_token": "<unk>",
|
2013 |
+
"use_default_system_prompt": false
|
2014 |
+
}
|