Instructions to use bswift/RETfound_eyepacs_DR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bswift/RETfound_eyepacs_DR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bswift/RETfound_eyepacs_DR") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("bswift/RETfound_eyepacs_DR") model = AutoModelForImageClassification.from_pretrained("bswift/RETfound_eyepacs_DR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from bswift/RETfound_eyepacs_DR: direct link, hf CLI and curl.
- Browser
- Download file 176 Bytes
-
https://huggingface.co/bswift/RETfound_eyepacs_DR/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://bswift/RETfound_eyepacs_DR/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/bswift/RETfound_eyepacs_DR/resolve/main/preprocessor_config.json
176 Bytes
| { | |
| "preprocess": { | |
| "resize": [256, 256], | |
| "normalize": { | |
| "mean": [0.485, 0.456, 0.406], | |
| "std": [0.229, 0.224, 0.225] | |
| } | |
| } | |
| } |