From ac4c607d2952f04d2610436b430ec89290d03705 Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Tue, 14 Oct 2025 10:35:15 -0400 Subject: [PATCH] update changelog Signed-off-by: Vladimir Mandic --- CHANGELOG.md | 24 +++++++++++++++++++----- 1 file changed, 19 insertions(+), 5 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index e2dd66d08..2a0af3ba9 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,6 +2,21 @@ ## Update for 2025-10-14 +### Highlights for 2025-10-14 + +It's been a month since the last release and number of changes is yet again massive with over 250 commits! +Highlight are: +- **Torch**: ROCm on Windows for AMD GPUs + if you have a compatible GPU, performance gains are significant! +- **Models**: + new WAN variants, a lot of new stuff with Qwen Image Edit including multi-image edits, expanded Nunchaku support and new SOTA upscaler with SeedVR2 + plus improved video support in general, including new methods of video encoding +- **Quantization**: + new **SVD**-style quantization using SDNQ ofers almost zero loss even with **4bit** quantization + and now you can also test your favorite quantization on-the-fly and then save/load model for future use + +### Details for 2025-10-14 + - **Models** - [WAN 2.2 14B VACE](https://huggingface.co/alibaba-pai/Wan2.2-VACE-Fun-A14B) available for *text-to-image* and *text-to-video* and *image-to-video* workflows @@ -19,10 +34,9 @@ updated version of E1 image editing model - [SeedVR2](https://iceclear.github.io/projects/seedvr/) originally designed for video restoration, seedvr works great for image detailing and upscaling! - available in 3B, 7B and 7B-sharp variants - use as any other upscaler! - note: seedvr is a very large model (6.4GB and 16GB respectively) and not designed for lower-end hardware - note: seedvr is highly sensitive to its cfg scale (set in settings -> postprocessing), + available in 3B, 7B and 7B-sharp variants, use as any other upscaler! + note: seedvr is a very large model (6.4GB and 16GB respectively) and not designed for lower-end hardware, quantization is highly recommended + note: seedvr is highly sensitive to its cfg scale, set in *settings -> postprocessing* lower values will result in smoother output while higher values add details - [X-Omni SFT](https://x-omni-team.github.io/) *experimental*: X-omni is a transformer-only discrete autoregressive image generative model trained with reinforcement learning @@ -101,7 +115,7 @@ - **video** new LTX model selection - replace `pynvml` with `nvidia-ml-py` for gpu monitoring - update **loopback** script with radon seed option, thanks @rabanti - - **vae** slicing enable for lowvram/medvram, tiling for lowvram, both disabled otherwise + - **vae** slicing enable for *lowvram/medvram*, tiling for *lowvram*, both disabled otherwise - **attention** remove split-attention and add explicitly attention slicing enable/disable option enable in *settings -> compute settings* can be combined with sdp, enabling may improve stability when used on iGPU or shared memory systems