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--- |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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- NousResearch/Hermes-3-Llama-3.1-8B |
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- Replete-AI/Replete-LLM-V2-Llama-3.1-8b |
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base_model: |
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- NousResearch/Hermes-3-Llama-3.1-8B |
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- Replete-AI/Replete-LLM-V2-Llama-3.1-8b |
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model-index: |
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- name: Herplete-LLM-Llama-3.1-8b |
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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: 46.72 |
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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=Etherll/Herplete-LLM-Llama-3.1-8b |
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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: 28.95 |
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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=Etherll/Herplete-LLM-Llama-3.1-8b |
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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: 2.79 |
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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=Etherll/Herplete-LLM-Llama-3.1-8b |
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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: 4.81 |
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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=Etherll/Herplete-LLM-Llama-3.1-8b |
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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: 6.68 |
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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=Etherll/Herplete-LLM-Llama-3.1-8b |
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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: 27.57 |
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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=Etherll/Herplete-LLM-Llama-3.1-8b |
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name: Open LLM Leaderboard |
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--- |
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# Herplete-LLM-Llama-3.1-8b |
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Herplete-LLM-Llama-3.1-8b is a continuous finetuned model from Replete-AI/Replete-LLM-V2-Llama-3.1-8b using Lora extracted from Hermes-3-Llama-3.1-8B. |
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You can find the continuous finetuning method here: |
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https://docs.google.com/document/d/1OjbjU5AOz4Ftn9xHQrX3oFQGhQ6RDUuXQipnQ9gn6tU/edit?usp=sharing |
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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 = "Etherll/Herplete-LLM-Llama-3.1-8b" |
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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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``` |
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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_Etherll__Herplete-LLM-Llama-3.1-8b) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |19.59| |
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|IFEval (0-Shot) |46.72| |
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|BBH (3-Shot) |28.95| |
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|MATH Lvl 5 (4-Shot)| 2.79| |
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|GPQA (0-shot) | 4.81| |
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|MuSR (0-shot) | 6.68| |
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|MMLU-PRO (5-shot) |27.57| |
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