Image Classification
Transformers
Safetensors
vit
vision transformer
agriculture
plant disease detection
smart farming
image classification
Instructions to use aashituli/promblemo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aashituli/promblemo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aashituli/promblemo") 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("aashituli/promblemo") model = AutoModelForImageClassification.from_pretrained("aashituli/promblemo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9dc1659cc2b62ef1f797daacab8aa24cc7d9b33f9da378419c4a10cd019e6d3b
- Size of remote file:
- 22.1 MB
- SHA256:
- 1f91c9032e290d145bec27d8b82439bc9ea189f4c72923740daf4113990314b2
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