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README.md
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* Architecture: Phi-3 Mini has 3.8B parameters and is a dense decoder-only Transformer model. The model is fine-tuned with Supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) to ensure alignment with human preferences and safety guidlines.
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* Inputs: Text. It is best suited for prompts using chat format.
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* Context length:
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* GPUS: 512 H100-80G
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* Training time: 7 days
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* Training data: 3.3T tokens
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* Architecture: Phi-3 Mini has 3.8B parameters and is a dense decoder-only Transformer model. The model is fine-tuned with Supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) to ensure alignment with human preferences and safety guidlines.
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* Inputs: Text. It is best suited for prompts using chat format.
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* Context length: 4K tokens
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* GPUS: 512 H100-80G
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* Training time: 7 days
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* Training data: 3.3T tokens
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