Instructions to use SixAILab/nepa-large-patch14-224-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SixAILab/nepa-large-patch14-224-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SixAILab/nepa-large-patch14-224-sft") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import ViTNepaForImageClassification model = ViTNepaForImageClassification.from_pretrained("SixAILab/nepa-large-patch14-224-sft", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and explicit GitHub link to model card
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
pipeline_tag: image-classificationto the metadata, which helps users discover the model via the Hugging Face Hub's filter system and enables a direct "Use in Transformers" widget. - Including an explicit link to the GitHub repository for easier access to the code.
Please review and merge if these updates look good.
sihanxu changed pull request status to merged