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--- |
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language: |
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- en |
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library_name: transformers |
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license: other |
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license_name: microsoft-terms-of-use |
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license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE |
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tags: |
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- text-generation-inference |
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- phi3 |
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- awq |
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- microsoft |
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extra_gated_heading: Access Microsoft on Hugging Face |
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extra_gated_prompt: >- |
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To access Phi-3 on Hugging Face, you’re required to review and agree to |
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Microsoft usage license. To do this, please ensure you’re logged-in to Hugging |
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Face and click below. Requests are processed immediately. |
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extra_gated_button_content: Acknowledge license |
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--- |
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1kFznlPlWYOrcgd7Q1NI2tYMLH_vTRuys?usp=sharing) |
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# phi-3-mini-4k-instruct-awq-4bit |
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phi-3-mini-4k-instruct-awq-4bit is a version of the [Microsoft](https://huggingface.co/microsoft) [Phi 3 mini 4k Instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) model that was quantized using the AWQ method developed by [Lin et al. (2023)](https://arxiv.org/abs/2306.00978). |
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Please refer to the [Original Phi 3 mini model card](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) for details about the model preparation and training processes. |
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## Dependencies |
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- [`autoawq==0.2.5`](https://pypi.org/project/autoawq/0.2.5/) – [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) was used to quantize the phi-3 model. |
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- [`vllm==0.4.2`](https://pypi.org/project/vllm/0.4.2/) – [vLLM](https://github.com/vllm-project/vllm) was used to host models for benchmarking. |