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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": ["BlockNet10"], | |
| "hidden_size": 1024, | |
| "num_classes": 10, | |
| "model_type": "custom_model" | |
| } | |