Instructions to use siddheshtv/BlockNet10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siddheshtv/BlockNet10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="siddheshtv/BlockNet10") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import BlockNet10 model = BlockNet10.from_pretrained("siddheshtv/BlockNet10", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| data/ | |
| push_to_hf.py | |
| *.ipynb |