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README.md
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### Model
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* Architecture: Phi-3 Small-8K-Instruct has 7B 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: 8K tokens
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* GPUs: 1024 H100-80G
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* [Triton](https://github.com/openai/triton)
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## Hardware
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Note that by default, the Phi-3-Small model uses flash attention, which requires certain types of GPU hardware to run. We have tested on the following GPU types:
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* NVIDIA A100
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* NVIDIA A6000
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* NVIDIA H100
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### Model
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* Architecture: Phi-3 Small-8K-Instruct has 7B parameters and is a dense decoder-only Transformer model with alternating dense and blocksparse attentions. 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: 8K tokens
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* GPUs: 1024 H100-80G
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* [Triton](https://github.com/openai/triton)
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## Hardware
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Note that by default, the Phi-3-Small model uses flash attention 2 and Triton blocksparse attention, which requires certain types of GPU hardware to run. We have tested on the following GPU types:
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* NVIDIA A100
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* NVIDIA A6000
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* NVIDIA H100
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