Instructions to use prithivMLmods/Fire-Detection-Siglip2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Fire-Detection-Siglip2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Fire-Detection-Siglip2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Fire-Detection-Siglip2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Fire-Detection-Siglip2") - Notebooks
- Google Colab
- Kaggle
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README.md
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- **Class 1:** "Normal" – The image depicts a normal, fire-free environment.
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- **Class 2:** "Smoke" – The image contains visible smoke, indicating potential fire risk.
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```python
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!pip install -q transformers torch pillow gradio
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```
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- **Class 1:** "Normal" – The image depicts a normal, fire-free environment.
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- **Class 2:** "Smoke" – The image contains visible smoke, indicating potential fire risk.
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# **Run with Transformers🤗**
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```python
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!pip install -q transformers torch pillow gradio
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```
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