Instructions to use SixAILab/nepa-base-patch14-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SixAILab/nepa-base-patch14-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="SixAILab/nepa-base-patch14-224")# Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("SixAILab/nepa-base-patch14-224", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, GitHub link, and update project page URL
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
pipeline_tag: image-feature-extractionto the metadata, which helps users discover the model on the Hugging Face Hub under relevant tasks and enables the automated "Use in Transformers" widget. - Adding an explicit GitHub badge for easier access to the code repository: https://github.com/SihanXU/nepa.
- Updating the project page URL in the existing badge to
https://sihanxu.me/nepato reflect the provided official project page.
sihanxu changed pull request status to merged