lllyasviel / lllyasviel/FramePack
Does not work on Nvidia 1080 8GB
- Dominant language
- Python
- Stars
- 17.3k
- Forks
- 1.7k
- PR merge metrics
- No merged PRs in 30d
Description
Although it is claimed that this program only needs 6 GB of VRAM I get the following error:
Currently enabled native sdp backends: ['flash', 'math', 'mem_efficient', 'cudnn']
Xformers is not installed!
Flash Attn is not installed!
Sage Attn is not installed!
Namespace(share=False, server='127.0.0.1', port=None, inbrowser=True)
Free VRAM 7.0185546875 GB
High-VRAM Mode: False
Downloading shards: 100%|██████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 4013.69it/s]
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 8.51it/s]
Fetching 3 files: 100%|██████████████████████████████████████████████████████████████████████████| 3/3 [00:00
Contributor guide
No contributing guide indexed for this repository
Research direction
Reproduce the failure from webui/demo_gradio.py, then read the attention path in webui/diffusers_helper/models/hunyuan_video_packed.py and the sampler entry in webui/diffusers_helper/k_diffusion/k_diffusion_hunyuan.py. Compare the reported VRAM state with the scaled dot-product attention call; done means the reported 8 GB configuration completes generation without the shown CUDA out-of-memory error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100