204 lines
5.6 KiB
Markdown
204 lines
5.6 KiB
Markdown
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---
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license: apache-2.0
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tags:
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- merge
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- mergekit
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- lazymergekit
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base_model:
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- Intel/neural-chat-7b-v3-3
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- openaccess-ai-collective/DPOpenHermes-7B-v2
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- fblgit/una-cybertron-7b-v2-bf16
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- openchat/openchat-3.5-0106
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- OpenPipe/mistral-ft-optimized-1227
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- mlabonne/NeuralHermes-2.5-Mistral-7B
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model-index:
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- name: Darewin-7B
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 68.6
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Darewin-7B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 86.22
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Darewin-7B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 65.21
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Darewin-7B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 60.38
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Darewin-7B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 79.79
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Darewin-7B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 71.04
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Darewin-7B
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name: Open LLM Leaderboard
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---
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# Darewin-7B
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Darewin-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3)
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* [openaccess-ai-collective/DPOpenHermes-7B-v2](https://huggingface.co/openaccess-ai-collective/DPOpenHermes-7B-v2)
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* [fblgit/una-cybertron-7b-v2-bf16](https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16)
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* [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106)
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* [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227)
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* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
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## 🧩 Configuration
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```yaml
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models:
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- model: mistralai/Mistral-7B-v0.1
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# No parameters necessary for base model
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- model: Intel/neural-chat-7b-v3-3
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parameters:
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density: 0.6
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weight: 0.2
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- model: openaccess-ai-collective/DPOpenHermes-7B-v2
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parameters:
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density: 0.6
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weight: 0.1
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- model: fblgit/una-cybertron-7b-v2-bf16
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parameters:
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density: 0.6
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weight: 0.2
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- model: openchat/openchat-3.5-0106
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parameters:
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density: 0.6
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weight: 0.15
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- model: OpenPipe/mistral-ft-optimized-1227
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parameters:
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density: 0.6
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weight: 0.25
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- model: mlabonne/NeuralHermes-2.5-Mistral-7B
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parameters:
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density: 0.6
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weight: 0.1
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merge_method: dare_ties
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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int8_mask: true
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dtype: bfloat16
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "mlabonne/Darewin-7B"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__Darewin-7B)
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| Metric |Value|
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|Avg. |71.87|
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|AI2 Reasoning Challenge (25-Shot)|68.60|
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|HellaSwag (10-Shot) |86.22|
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|MMLU (5-Shot) |65.21|
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|TruthfulQA (0-shot) |60.38|
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|Winogrande (5-shot) |79.79|
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|GSM8k (5-shot) |71.04|
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