Instructions to use EdBianchi/vit-fire-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EdBianchi/vit-fire-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="EdBianchi/vit-fire-detection") 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("EdBianchi/vit-fire-detection") model = AutoModelForImageClassification.from_pretrained("EdBianchi/vit-fire-detection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 6
Browse files
pytorch_model.bin
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runs/Feb05_15-42-37_Edoardos-MacBook-Pro.local/events.out.tfevents.1675608175.Edoardos-MacBook-Pro.local.40210.0
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