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| | inference: false |
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| | # nbeerbower/phi3.5-gutenberg-4B AWQ |
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| | ** PROCESSING .... ETA 30mins ** |
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| | - Model creator: [nbeerbower](https://huggingface.co/nbeerbower) |
| | - Original model: [phi3.5-gutenberg-4B](https://huggingface.co/nbeerbower/phi3.5-gutenberg-4B) |
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| | ### About AWQ |
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| | AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings. |
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| | AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead. |
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| | It is supported by: |
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| | - [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ |
| | - [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types. |
| | - [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference) |
| | - [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers |
| | - [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code |
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