72 lines
1.9 KiB
Markdown
72 lines
1.9 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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---
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# mistral-7b-merged-dare
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mistral-7b-merged-dare is a merge of the following models:
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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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- model: samir-fama/SamirGPT-v1
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parameters:
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density: 0.53
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weight: 0.4
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- model: abacusai/Slerp-CM-mist-dpo
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parameters:
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density: 0.53
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weight: 0.3
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- model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
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parameters:
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density: 0.53
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weight: 0.3
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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 bitsandbytes 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 = "mayacinka/West-Ramen-7Bx4"
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tokenizer = AutoTokenizer.from_pretrained(model)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
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)
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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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_mychen76__mistral-7b-merged-dare)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |73.46|
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|AI2 Reasoning Challenge (25-Shot)|69.71|
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|HellaSwag (10-Shot) |87.05|
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|MMLU (5-Shot) |65.07|
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|TruthfulQA (0-shot) |63.24|
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|Winogrande (5-shot) |81.61|
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|GSM8k (5-shot) |73.01|
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