Instructions to use dima806/mushrooms_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/mushrooms_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/mushrooms_image_detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("dima806/mushrooms_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/mushrooms_image_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aff0ea51dfc854cdab7f5363ce6d56088b9a98176605199892a2ca194b32b346
- Size of remote file:
- 4.41 kB
- SHA256:
- 14e33a4db2571bfd726f0a6cd67bd082eae6cbf665dbb7c1181326245dfc0e7a
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