Instructions to use xiaoxiaxu/LowLatencyMEG_Backbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xiaoxiaxu/LowLatencyMEG_Backbone with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xiaoxiaxu/LowLatencyMEG_Backbone", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download MEG_decoder.pth from xiaoxiaxu/LowLatencyMEG_Backbone: direct link, hf CLI and curl.
- Browser
- Download file 99 MB
-
https://huggingface.co/xiaoxiaxu/LowLatencyMEG_Backbone/resolve/main/MEG_decoder.pth
- Command line
-
hf download hf://xiaoxiaxu/LowLatencyMEG_Backbone/MEG_decoder.pth
-
curl -L -o MEG_decoder.pth https://huggingface.co/xiaoxiaxu/LowLatencyMEG_Backbone/resolve/main/MEG_decoder.pth
99 MB
- Xet hash:
- a602930e7d8fa1fc56010f9770a0c0f1dc0442b3304c450a587170adf37eeb30
- Size of remote file:
- 99 MB
- SHA256:
- 00994d78e531c1c8bd480ed4e05a0035eab0ad9e78b87d9673902ca3e16ea0b2
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