Instructions to use bytedance-research/UNO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bytedance-research/UNO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="bytedance-research/UNO")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bytedance-research/UNO", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Correct pipeline tag and add library name
#1
by nielsr HF Staff - opened
This PR corrects the pipeline_tag to image-to-image to accurately reflect the model's functionality. It also adds the library_name tag as transformers to better describe the model's compatibility.
fenfan changed pull request status to merged