Image Classification
Transformers
TensorBoard
Safetensors
vit
vision-transformer
aquaculture
fish-disease
Generated from Trainer
Eval Results (legacy)
Instructions to use panda992/fish_disease_datasets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use panda992/fish_disease_datasets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="panda992/fish_disease_datasets") 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("panda992/fish_disease_datasets") model = AutoModelForImageClassification.from_pretrained("panda992/fish_disease_datasets", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90e9caa2804ae0cb25d476568666271f4a12dc17dcf33737355ce7357753769f
- Size of remote file:
- 5.71 kB
- SHA256:
- 22c558d357f8503f09837523ab362f68d4f825ddc17609dfdba8f98aaba50040
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