Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
将大型语言模型(LLM)量化为 8 位或 4 位,以实现 50-75% 的内存减少,同时损失很小的准确性。当 GPU 内存有限、需要适应更大模型或希望加快推理速度时使用。支持 INT8、NF4、FP4 格式、QLoRA 训练和 8 位优化器。与 HuggingFace Transformers 一起使用。
Category: developer (开发工具) · Author: davila7 · Version: @main · License: MIT
Tags: Optimization, Bitsandbytes, Quantization, 8-Bit, 4-Bit, Memory Optimization, QLoRA, NF4, INT8, HuggingFace, Efficient Inference
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Category:developer
Tags:Optimization, Bitsandbytes, Quantization, 8-Bit, 4-Bit, Memory Optimization, QLoRA, NF4, INT8, HuggingFace, Efficient Inference