Image Classification
PyTorch
Safetensors
Transformers
English
resnet10
feature-extraction
jax-conversion
resnet
hil-serl
Lerobot
vision
custom_code
Instructions to use lerobot/resnet10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lerobot/resnet10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lerobot/resnet10", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lerobot/resnet10", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "ResNet10" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_resnet.ResNet10Config", | |
| "AutoModel": "modeling_resnet.ResNet10" | |
| }, | |
| "depths": [ | |
| 1, | |
| 1, | |
| 1, | |
| 1 | |
| ], | |
| "dtype": "float32", | |
| "embedding_size": 64, | |
| "hidden_act": "relu", | |
| "hidden_sizes": [ | |
| 64, | |
| 128, | |
| 256, | |
| 512 | |
| ], | |
| "model_type": "resnet10", | |
| "num_channels": 3, | |
| "pooler": null, | |
| "transformers_version": "5.3.0" | |
| } | |