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| # Quantization | |
| Quantization techniques reduce memory and computational costs by representing weights and activations with lower-precision data types like 8-bit integers (int8). This enables loading larger models you normally wouldn't be able to fit into memory, and speeding up inference. Diffusers supports 8-bit and 4-bit quantization with [bitsandbytes](https://huggingface.co/docs/bitsandbytes/en/index). | |
| Quantization techniques that aren't supported in Transformers can be added with the [`DiffusersQuantizer`] class. | |
| <Tip> | |
| Learn how to quantize models in the [Quantization](../quantization/overview) guide. | |
| </Tip> | |
| ## BitsAndBytesConfig | |
| [[autodoc]] BitsAndBytesConfig | |
| ## DiffusersQuantizer | |
| [[autodoc]] quantizers.base.DiffusersQuantizer | |