CorticalStack/mistral-7b-openhermes-awq
CorticalStack/mistral-7b-openhermes-awq is an AWQ quantised version of CorticalStack/mistral-7b-openhermes-sft.
About AWQ
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.
AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.
It is supported by:
- Text Generation Webui - using Loader: AutoAWQ
- vLLM - version 0.2.2 or later for support for all model types.
- Hugging Face Text Generation Inference (TGI)
- Transformers version 4.35.0 and later, from any code or client that supports Transformers
- AutoAWQ - for use from Python code
AWQ configuration
- Zero point: True
- Q group size: 128
- W bit: 4
- Version: GEMM
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