diffusers
https://github.com/huggingface/diffusers
Python
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
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- Issues
- Propose translation to romanian for the diffusers hugging face course
- Stop passing fps to the transformer in Cosmos2VideoToWorldPipeline
- Fix missing cache contexts in Wan video-to-video
- Compute QwenImage-2.1 timestep frequencies in fp32
- Qwen-Image-2.1 VAE tiling: RGB/alpha seams and a full-context decode workaround on ROCm
- `CosmosTransformer3DModel.from_single_file()` does not work with the `model.diffusion_model.` prefix
- `from_single_file()` support for AnimaTextConditioner
- Anima `from_single_file()` fix for models with `model.diffusion_model` prefix, and strip all `llm_adapter` keys
- StableAudio3DiTModel: loading with torch_dtype=bf16/fp16 collapses RoPE positions (arange built in inv_freq dtype)
- QwenImage21: model.to(bf16) (as in train_dreambooth_lora_qwenimage21.py) rounds the timestep-embedding freqs buffer, so LoRA training sees a different embedding than inference
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