Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use hanad/self_harm_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanad/self_harm_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hanad/self_harm_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("hanad/self_harm_detection") model = AutoModelForImageClassification.from_pretrained("hanad/self_harm_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdc47a1db5882a1691d7af69c413482a7fb0413f5e89d637d52a36c0f9bb6c5c
- Size of remote file:
- 5.11 kB
- SHA256:
- 41b69d76824e72f4d4988db976c9018c75fee5a5a5d978f9da2a32e40ab8f1e8
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