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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ ---
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+
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+ # CorticalStack/pastiche-crown-clown-7b-dare-dpo-awq
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+
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+ CorticalStack/pastiche-crown-clown-7b-dare-dpo-awq is an AWQ quantised version of [CorticalStack/pastiche-crown-clown-7b-dare-dpo](https://huggingface.co/CorticalStack/pastiche-crown-clown-7b-dare-dpo).
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+
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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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+
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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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+
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+ It is supported by:
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+
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+ - [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ
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+ - [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types.
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+ - [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference)
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+ - [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers
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+ - [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code
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+
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+ ### AWQ configuration
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+ - Zero point: True
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+ - Q group size: 128
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+ - W bit: 4
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+ - Version: GEMM
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+ "quant_method": "awq",
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