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:
- 49a48e59d25891125464dcd1dc6498d3a1cd196f60dc1f91dd6455c2de9224ca
- Size of remote file:
- 344 MB
- SHA256:
- 9b0731161efd47de6909e594bb48a5524ce47db4a0dbb179fb24599c1131f88c
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