Instructions to use Madronus/deciduous-conifer-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madronus/deciduous-conifer-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Madronus/deciduous-conifer-classifier") 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("Madronus/deciduous-conifer-classifier") model = AutoModelForImageClassification.from_pretrained("Madronus/deciduous-conifer-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Madronus/deciduous-conifer-classifier: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Madronus/deciduous-conifer-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Madronus/deciduous-conifer-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Madronus/deciduous-conifer-classifier/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- af345896b782eb5f83c66188c20fd9e652fca152d1695e74590d0a5a0592be5c
- Size of remote file:
- 343 MB
- SHA256:
- 8d3f8b86837bd3bbe00d085475956fd8898f5151b17cbf829602325263a80659
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