Chat & support: TheBloke’s Discord server Want to contribute? TheBloke’s Patreon page TheBloke’s LLM work is generously supported by a grant from andreessen horowitz (a16z) This repo contains AWQ model files for CausalLM’s CausalLM 7B. 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. — Text Generation Webui — using Loader: AutoAWQ — vLLM — Llama and Mistral models only — Hugging Face Text Generation Inference (TGI) — AutoAWQ — for use from Python code AWQ model(s) for GPU inference. GPTQ models for GPU inference, with multiple quantisation parameter options. 2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference CausalLM’s original unquantised fp16 model in pytorch format, for GPU inference and for further conversions The creator of the source model has listed its license as wtfpl, and this quantization has therefore used that same license. As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: TheBloke
Теги: llama, llama2, qwen, en, zh, text-generation-inference, 4-bit, awq
Лайков: 3 | Загрузок: 18
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
