- GGUF now works and included 4 bit quants, this will allow WAN to run on 24GB VRAM GPUs
- logger only shows full stack for errors
- helper functions for colab notebook
- fix nvcr.io auth error
- lora issues are now reported better
- model downloader will use huggingface cache and symlinking if it is supported on your platform
- torch compile node now correctly patches the model before compilation
- add xet support and add the xet cache to manageable directories
- xet is enabled by default
- fix logging to root in various places
- improve logging about model unloading and loading
- TorchCompileNode now supports the VAE
- torchaudio missing will cause less noise in the logs
- feature flags will assume to be supporting everything in the distributed progress context
- fixes progress notifications
* [moonvalley] Update V2V node to match API specification
- Add exact resolution validation for supported resolutions (1920x1080, 1080x1920, 1152x1152, 1536x1152, 1152x1536)
- Change frame count validation from divisible by 32 to 16
- Add MP4 container format validation
- Remove internal parameters (steps, guidance_scale) from V2V inference params
- Update video duration handling to support only 5 seconds (auto-trim if longer)
- Add motion_intensity parameter (0-100) for Motion Transfer control type
- Add get_container_format() method to VideoInput classes
* update negative prompt
* Added the parameter required_frontend_version in the /system_stats api response
* Update server.py
* Created a function get_required_frontend_version and wrote tests for it
* Refactored the function to return currently installed frontend pacakage version
* Moved required_frontend to a new function and imported that in server.py
* Corrected test cases using mocking techniques
* Corrected files to comply with ruff formatting
* Add factorization utils for lokr
* Add lokr train impl
* Add loha train impl
* Add adapter map for algo selection
* Add optional grad ckpt and algo selection
* Update __init__.py
* correct key name for loha
* Use custom fwd/bwd func and better init for loha
* Support gradient accumulation
* Fix bugs of loha
* use more stable init
* Add OFT training
* linting
