Add quant links
#2
by
bartowski
- opened
README.md
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## Training Data
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The `Locutusque/Hyperion-3.0-Mistral-7B-DPO` model was fine-tuned on a carefully curated dataset of 20,000 preference pairs, where 4,000 examples were used to fine-tune. These examples were generated by GPT-4 to ensure the highest quality and relevance across various domains, including programming, medical texts, mathematical problems, and reasoning tasks. The training data was further optimized using Direct Preference Optimization (DPO) to align the model's outputs with human preferences and improve overall performance.
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## Evaluation Results
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mmlu flan cot 5-shot
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## Training Data
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The `Locutusque/Hyperion-3.0-Mistral-7B-DPO` model was fine-tuned on a carefully curated dataset of 20,000 preference pairs, where 4,000 examples were used to fine-tune. These examples were generated by GPT-4 to ensure the highest quality and relevance across various domains, including programming, medical texts, mathematical problems, and reasoning tasks. The training data was further optimized using Direct Preference Optimization (DPO) to align the model's outputs with human preferences and improve overall performance.
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## Quants
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ExLlamaV2: https://huggingface.co/bartowski/Hyperion-3.0-Mistral-7B-DPO-exl2
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GGUF: https://huggingface.co/bartowski/Hyperion-3.0-Mistral-7B-DPO-GGUF
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## Evaluation Results
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mmlu flan cot 5-shot
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