Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use muhnatha/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhnatha/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="muhnatha/image_classification") 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("muhnatha/image_classification") model = AutoModelForImageClassification.from_pretrained("muhnatha/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eecea7fdc8cfda320d972c9cddea8e214c7032eabb62035035e5d4626069f173
- Size of remote file:
- 4.6 kB
- SHA256:
- 27072e20fd052c561cf912436670d4d067a003f14a9d2a98bbfe5a77ae8d68c3
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