Instructions to use whj363636/SPTNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whj363636/SPTNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="whj363636/SPTNet") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("whj363636/SPTNet", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library name; include link to Github repository
#1
by nielsr HF Staff - opened
This PR adds the image-classification pipeline tag, ensuring people can find your model at https://huggingface.co/models?pipeline_tag=image-classification.
It also specifies the transformers library and includes a direct link to the Github repository for easier access to the code.
whj363636 changed pull request status to merged