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Eagle-X5-7B-AWQ
solidrust/Eagle-X5-7B-AWQ
Eagle-X5-7B-AWQ is a machine learning model from solidrust. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Updated Sep 3, 2024
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At a glance
- Access
- Public
- Created
- Sep 3, 2024
- Updated
- Sep 3, 2024
- SHA
- 0ead14d9
Model card
From the Hugging Face model README
NVEagle/Eagle-X5-7B AWQ
** PROCESSING .... ETA 30mins **
- Model creator: NVEagle
- Original model: Eagle-X5-7B
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
- Created
- Sep 3, 2024
- Updated
- Sep 3, 2024