quantizing-models-bitsandbytes

SKILLWorkflowcommunity
v0.0.0Orchestra-ResearchMITUpdated 2mo agoSource →

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.

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2mo agoLast update
Skill
AuthorOrchestra-Research
Version0.0.0
LicenseMIT
CategoryWorkflow
Formatsskill.md
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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.

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