diffusers/examples/research_projects/intel_opts
Naoki Ainoya 14e3a28c12
Rename 'CLIPFeatureExtractor' class to 'CLIPImageProcessor' (#2732)
The 'CLIPFeatureExtractor' class name has been renamed to 'CLIPImageProcessor' in order to comply with future deprecation. This commit includes the necessary changes to the affected files.
2023-03-23 13:49:22 +01:00
..
textual_inversion Rename 'CLIPFeatureExtractor' class to 'CLIPImageProcessor' (#2732) 2023-03-23 13:49:22 +01:00
README.md Add examples with Intel optimizations (#1579) 2022-12-15 21:16:27 +01:00
inference_bf16.py Replace flake8 with ruff and update black (#2279) 2023-02-07 23:46:23 +01:00

README.md

Diffusers examples with Intel optimizations

This research project is not actively maintained by the diffusers team. For any questions or comments, please make sure to tag @hshen14 .

This aims to provide diffusers examples with Intel optimizations such as Bfloat16 for training/fine-tuning acceleration and 8-bit integer (INT8) for inference acceleration on Intel platforms.

Accelerating the fine-tuning for textual inversion

We accelereate the fine-tuning for textual inversion with Intel Extension for PyTorch. The examples enable both single node and multi-node distributed training with Bfloat16 support on Intel Xeon Scalable Processor.

Accelerating the inference for Stable Diffusion using Bfloat16

We start the inference acceleration with Bfloat16 using Intel Extension for PyTorch. The script is generally designed to support standard Stable Diffusion models with Bfloat16 support.

Accelerating the inference for Stable Diffusion using INT8

Coming soon ...