Image Classification
Transformers
Safetensors
English
siglip
Forest-Fire-Detection
SigLIP2
climate
Smoke
Normal
Fire
Instructions to use prithivMLmods/Forest-Fire-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Forest-Fire-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Forest-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 AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Forest-Fire-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Forest-Fire-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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import torch
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# Load model and processor
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model_name = "prithivMLmods/
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model = SiglipForImageClassification.from_pretrained(model_name)
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processor = AutoImageProcessor.from_pretrained(model_name)
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import torch
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# Load model and processor
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model_name = "prithivMLmods/Forest-Fire-Detection" # Update with actual model name on Hugging Face
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model = SiglipForImageClassification.from_pretrained(model_name)
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processor = AutoImageProcessor.from_pretrained(model_name)
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