Instructions to use hypha-space/lenet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hypha-space/lenet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hypha-space/lenet", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("hypha-space/lenet", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 314 Bytes
ba44f26 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"architectures": [
"LeNetModelForImageClassification"
],
"auto_map": {
"AutoConfig": "configuration_lenet.LeNetConfig",
"AutoModelForImageClassification": "modeling_lenet.LeNetModelForImageClassification"
},
"dtype": "float32",
"model_type": "lenet",
"transformers_version": "4.57.1"
}
|