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Model: mlabonne/ChimeraLlama-3-8B-v2 Source: Original Platform
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README.md
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README.md
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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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base_model:
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- NousResearch/Meta-Llama-3-8B-Instruct
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- mlabonne/OrpoLlama-3-8B
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- cognitivecomputations/dolphin-2.9-llama3-8b
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- Locutusque/llama-3-neural-chat-v1-8b
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- cloudyu/Meta-Llama-3-8B-Instruct-DPO
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- vicgalle/Configurable-Llama-3-8B-v0.3
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model-index:
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- name: ChimeraLlama-3-8B-v2
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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: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 44.69
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/ChimeraLlama-3-8B-v2
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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: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 28.48
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/ChimeraLlama-3-8B-v2
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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: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 8.31
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/ChimeraLlama-3-8B-v2
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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: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 4.7
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/ChimeraLlama-3-8B-v2
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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: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 5.25
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/ChimeraLlama-3-8B-v2
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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-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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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: 28.54
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/ChimeraLlama-3-8B-v2
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name: Open LLM Leaderboard
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---
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# ChimeraLlama-3-8B-v2
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ChimeraLlama-3-8B-v2 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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* [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b)
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* [Locutusque/llama-3-neural-chat-v1-8b](https://huggingface.co/Locutusque/llama-3-neural-chat-v1-8b)
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* [cloudyu/Meta-Llama-3-8B-Instruct-DPO](https://huggingface.co/cloudyu/Meta-Llama-3-8B-Instruct-DPO)
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* [vicgalle/Configurable-Llama-3-8B-v0.3](https://huggingface.co/vicgalle/Configurable-Llama-3-8B-v0.3)
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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: 0.6
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weight: 0.55
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- model: mlabonne/OrpoLlama-3-8B
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parameters:
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density: 0.55
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weight: 0.05
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- model: cognitivecomputations/dolphin-2.9-llama3-8b
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parameters:
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density: 0.55
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weight: 0.1
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- model: Locutusque/llama-3-neural-chat-v1-8b
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parameters:
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density: 0.55
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weight: 0.05
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- model: cloudyu/Meta-Llama-3-8B-Instruct-DPO
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parameters:
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density: 0.55
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weight: 0.15
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- model: vicgalle/Configurable-Llama-3-8B-v0.3
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parameters:
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density: 0.55
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weight: 0.1
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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-v2"
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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/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__ChimeraLlama-3-8B-v2)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |19.99|
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|IFEval (0-Shot) |44.69|
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|BBH (3-Shot) |28.48|
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|MATH Lvl 5 (4-Shot)| 8.31|
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|GPQA (0-shot) | 4.70|
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|MuSR (0-shot) | 5.25|
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|MMLU-PRO (5-shot) |28.54|
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