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
Download preprocessor_config.json from hypha-space/lenet: direct link, hf CLI and curl.
- Browser
- Download file 130 Bytes
-
https://huggingface.co/hypha-space/lenet/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://hypha-space/lenet/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/hypha-space/lenet/resolve/main/preprocessor_config.json
130 Bytes
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "preprocessor_lenet.LeNetProcessor" | |
| }, | |
| "image_processor_type": "LeNetProcessor" | |
| } | |