Instructions to use Shravanig/vit-fire-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shravanig/vit-fire-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Shravanig/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("Shravanig/vit-fire-detection") model = AutoModelForImageClassification.from_pretrained("Shravanig/vit-fire-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 4
Browse files
model.safetensors
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runs/Feb04_13-55-06_Shravani/events.out.tfevents.1707035107.Shravani.10068.0
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