Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use surprisedPikachu007/tomato-disease-detection_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use surprisedPikachu007/tomato-disease-detection_V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="surprisedPikachu007/tomato-disease-detection_V2") 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("surprisedPikachu007/tomato-disease-detection_V2") model = AutoModelForImageClassification.from_pretrained("surprisedPikachu007/tomato-disease-detection_V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from surprisedPikachu007/tomato-disease-detection_V2: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/surprisedPikachu007/tomato-disease-detection_V2/resolve/1bb3e012f97759ece16fcba2e1ff77295af3c7b0/training_args.bin
- Command line
-
hf download hf://surprisedPikachu007/tomato-disease-detection_V2@1bb3e012f97759ece16fcba2e1ff77295af3c7b0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/surprisedPikachu007/tomato-disease-detection_V2/resolve/1bb3e012f97759ece16fcba2e1ff77295af3c7b0/training_args.bin
3.52 kB
- Xet hash:
- 1ad51e18a417abb7b6192eb5e75c0ec4b3a9899eb08ebe5d416d561392e7b7f9
- Size of remote file:
- 3.52 kB
- SHA256:
- b461627f306ee1a5f1c5a1451e955aa658afd1f95ef0918a50cb5248179277c0
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