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--- |
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license: llama3.1 |
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library_name: transformers |
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base_model: |
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- flammenai/Llama3.1-Flammades-70B |
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datasets: |
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- flammenai/MahouMix-v1 |
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model-index: |
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- name: Mahou-1.5-llama3.1-70B |
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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: 71.47 |
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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=flammenai/Mahou-1.5-llama3.1-70B |
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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: 52.37 |
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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=flammenai/Mahou-1.5-llama3.1-70B |
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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: 13.14 |
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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=flammenai/Mahou-1.5-llama3.1-70B |
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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: 13.87 |
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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=flammenai/Mahou-1.5-llama3.1-70B |
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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: 23.71 |
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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=flammenai/Mahou-1.5-llama3.1-70B |
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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: 41.66 |
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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=flammenai/Mahou-1.5-llama3.1-70B |
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name: Open LLM Leaderboard |
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--- |
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![image/png](https://huggingface.co/flammenai/Mahou-1.0-mistral-7B/resolve/main/mahou1.png) |
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# Mahou-1.5-llama3.1-70B |
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Mahou is designed to provide short messages in a conversational context. It is capable of casual conversation and character roleplay. |
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### Chat Format |
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This model has been trained to use ChatML format. |
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``` |
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<|im_start|>system |
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{{system}}<|im_end|> |
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<|im_start|>{{char}} |
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{{message}}<|im_end|> |
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<|im_start|>{{user}} |
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{{message}}<|im_end|> |
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``` |
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### Roleplay Format |
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- Speech without quotes. |
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- Actions in `*asterisks*` |
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``` |
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*leans against wall cooly* so like, i just casted a super strong spell at magician academy today, not gonna lie, felt badass. |
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``` |
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### SillyTavern Settings |
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1. Use ChatML for the Context Template. |
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2. Enable Instruct Mode. |
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3. Use the [Mahou ChatML Instruct preset](https://huggingface.co/datasets/flammenai/Mahou-ST-ChatML-Instruct/raw/main/Mahou.json). |
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4. Use the [Mahou Sampler preset](https://huggingface.co/datasets/flammenai/Mahou-ST-Sampler-Preset/raw/main/Mahou.json). |
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### Method |
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[ORPO finetuned](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) with 4x H100 for 3 epochs. |
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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_flammenai__Mahou-1.5-llama3.1-70B) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |36.04| |
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|IFEval (0-Shot) |71.47| |
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|BBH (3-Shot) |52.37| |
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|MATH Lvl 5 (4-Shot)|13.14| |
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|GPQA (0-shot) |13.87| |
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|MuSR (0-shot) |23.71| |
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|MMLU-PRO (5-shot) |41.66| |
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