Instructions to use shawnmichael/convnext-tiny-fire-smoke-detection-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shawnmichael/convnext-tiny-fire-smoke-detection-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="shawnmichael/convnext-tiny-fire-smoke-detection-v1") 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("shawnmichael/convnext-tiny-fire-smoke-detection-v1") model = AutoModelForImageClassification.from_pretrained("shawnmichael/convnext-tiny-fire-smoke-detection-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64a23e2e2ca7c34f153c2128c9ee1ae0ffc203e11032e0e2c766340bb9f14019
- Size of remote file:
- 5.37 kB
- SHA256:
- 7d1006590128c6a61de12eec4227fd71c54783d756815fb9b3677452473ba2b1
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