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:
- 743f62daa3fda750c50ea3cd5bcf7727a4ddc9f627bd2ba8b9df55e145a6ff04
- Size of remote file:
- 4.41 kB
- SHA256:
- dbe1b5c1ae744cd46bfc83fac7b8e6a1a1b6ccaf467352cf9058fbdc53c776f6
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