|
--- |
|
inference: false |
|
--- |
|
# rombodawg/Everyone-LLM-7b-Base AWQ |
|
|
|
** PROCESSING .... ETA 30mins ** |
|
|
|
- Model creator: [rombodawg](https://huggingface.co/rombodawg) |
|
- Original model: [Everyone-LLM-7b-Base](https://huggingface.co/rombodawg/Everyone-LLM-7b-Base) |
|
|
|
### 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](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 |
|
|
