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Top-Western-Maid-7B - GGUF
- Model creator: https://huggingface.co/saishf/
- Original model: https://huggingface.co/saishf/Top-Western-Maid-7B/
Name | Quant method | Size |
---|---|---|
Top-Western-Maid-7B.Q2_K.gguf | Q2_K | 2.53GB |
Top-Western-Maid-7B.IQ3_XS.gguf | IQ3_XS | 2.81GB |
Top-Western-Maid-7B.IQ3_S.gguf | IQ3_S | 2.96GB |
Top-Western-Maid-7B.Q3_K_S.gguf | Q3_K_S | 2.95GB |
Top-Western-Maid-7B.IQ3_M.gguf | IQ3_M | 3.06GB |
Top-Western-Maid-7B.Q3_K.gguf | Q3_K | 3.28GB |
Top-Western-Maid-7B.Q3_K_M.gguf | Q3_K_M | 3.28GB |
Top-Western-Maid-7B.Q3_K_L.gguf | Q3_K_L | 3.56GB |
Top-Western-Maid-7B.IQ4_XS.gguf | IQ4_XS | 3.67GB |
Top-Western-Maid-7B.Q4_0.gguf | Q4_0 | 3.83GB |
Top-Western-Maid-7B.IQ4_NL.gguf | IQ4_NL | 3.87GB |
Top-Western-Maid-7B.Q4_K_S.gguf | Q4_K_S | 3.86GB |
Top-Western-Maid-7B.Q4_K.gguf | Q4_K | 4.07GB |
Top-Western-Maid-7B.Q4_K_M.gguf | Q4_K_M | 4.07GB |
Top-Western-Maid-7B.Q4_1.gguf | Q4_1 | 4.24GB |
Top-Western-Maid-7B.Q5_0.gguf | Q5_0 | 4.65GB |
Top-Western-Maid-7B.Q5_K_S.gguf | Q5_K_S | 4.65GB |
Top-Western-Maid-7B.Q5_K.gguf | Q5_K | 4.78GB |
Top-Western-Maid-7B.Q5_K_M.gguf | Q5_K_M | 4.78GB |
Top-Western-Maid-7B.Q5_1.gguf | Q5_1 | 5.07GB |
Top-Western-Maid-7B.Q6_K.gguf | Q6_K | 5.53GB |
Top-Western-Maid-7B.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
license: cc-by-nc-4.0 tags: - mergekit - merge base_model: - NeverSleep/Noromaid-7B-0.4-DPO - Undi95/Toppy-M-7B - mistralai/Mistral-7B-v0.1 - senseable/WestLake-7B-v2 model-index: - name: Top-Western-Maid-7B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 69.37 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saishf/Top-Western-Maid-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 87.4 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saishf/Top-Western-Maid-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.63 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saishf/Top-Western-Maid-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 58.79 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saishf/Top-Western-Maid-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 83.27 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saishf/Top-Western-Maid-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 65.96 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saishf/Top-Western-Maid-7B name: Open LLM Leaderboard
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using mistralai/Mistral-7B-v0.1 as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: mistralai/Mistral-7B-v0.1
# No parameters necessary for base model
- model: senseable/WestLake-7B-v2
parameters:
density: 0.53
weight: 0.55
- model: NeverSleep/Noromaid-7B-0.4-DPO
parameters:
density: 0.53
weight: 0.30
- model: Undi95/Toppy-M-7B
parameters:
density: 0.53
weight: 0.15
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 71.57 |
AI2 Reasoning Challenge (25-Shot) | 69.37 |
HellaSwag (10-Shot) | 87.40 |
MMLU (5-Shot) | 64.63 |
TruthfulQA (0-shot) | 58.79 |
Winogrande (5-shot) | 83.27 |
GSM8k (5-shot) | 65.96 |
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