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--- |
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license: other |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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- llama |
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base_model: |
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- NousResearch/Meta-Llama-3-8B-Instruct |
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- mlabonne/OrpoLlama-3-8B |
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- Locutusque/Llama-3-Orca-1.0-8B |
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- abacusai/Llama-3-Smaug-8B |
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--- |
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# ChimeraLlama-3-8B |
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ChimeraLlama-3-8B outperforms Llama 3 8B Instruct on Nous' benchmark suite. |
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ChimeraLlama-3-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) |
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* [mlabonne/OrpoLlama-3-8B](https://huggingface.co/mlabonne/OrpoLlama-3-8B) |
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* [Locutusque/Llama-3-Orca-1.0-8B](https://huggingface.co/Locutusque/Llama-3-Orca-1.0-8B) |
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* [abacusai/Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B) |
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## 🏆 Evaluation |
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### Nous |
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Evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval), see the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard). |
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| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | |
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| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: | |
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| [**mlabonne/ChimeraLlama-3-8B**](https://huggingface.co/mlabonne/Chimera-8B) [📄](https://gist.github.com/mlabonne/28d31153628dccf781b74f8071c7c7e4) | **51.58** | **39.12** | **71.81** | **52.4** | **42.98** | |
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| [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [📄](https://gist.github.com/mlabonne/8329284d86035e6019edb11eb0933628) | 51.34 | 41.22 | 69.86 | 51.65 | 42.64 | |
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| [mlabonne/OrpoLlama-3-8B](https://huggingface.co/mlabonne/OrpoLlama-3-8B) [📄](https://gist.github.com/mlabonne/22896a1ae164859931cc8f4858c97f6f) | 48.63 | 34.17 | 70.59 | 52.39 | 37.36 | |
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| [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [📄](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847) | 45.42 | 31.1 | 69.95 | 43.91 | 36.7 | |
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## 🧩 Configuration |
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```yaml |
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models: |
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- model: NousResearch/Meta-Llama-3-8B |
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# No parameters necessary for base model |
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- model: NousResearch/Meta-Llama-3-8B-Instruct |
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parameters: |
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density: 0.58 |
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weight: 0.4 |
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- model: mlabonne/OrpoLlama-3-8B |
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parameters: |
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density: 0.52 |
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weight: 0.2 |
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- model: Locutusque/Llama-3-Orca-1.0-8B |
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parameters: |
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density: 0.52 |
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weight: 0.2 |
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- model: abacusai/Llama-3-Smaug-8B |
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parameters: |
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density: 0.52 |
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weight: 0.2 |
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merge_method: dare_ties |
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base_model: NousResearch/Meta-Llama-3-8B |
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parameters: |
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int8_mask: true |
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dtype: float16 |
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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/ChimeraLlama-3-8B" |
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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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``` |
