Instructions to use YUXU915/TAG-MoE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YUXU915/TAG-MoE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YUXU915/TAG-MoE", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
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Update README.md (#3)
- Update README.md (9e55d52a9cab39a4ab3b19d823ca10b58494ef6f) Co-authored-by: Yana-Hangabina <Yana-Hangabina@users.noreply.huggingface.co>860fb5a
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Update README.md (#2)
- Update README.md (c5562669c98588fa9c9f76f3b0f1746c336a78b4) Co-authored-by: Yana-Hangabina <Yana-Hangabina@users.noreply.huggingface.co>e45ccf6
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Release TAG-MoE weight (#1)
- Release weight (b61b56f85bd986a094b3cba69b60e7752144518e) Co-authored-by: Yana-Hangabina <Yana-Hangabina@users.noreply.huggingface.co>69569c3
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