Instructions to use callMeRover/fire_cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use callMeRover/fire_cv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="callMeRover/fire_cv") 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("callMeRover/fire_cv") model = AutoModelForImageClassification.from_pretrained("callMeRover/fire_cv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce304e24c921a61e644e61a292f683c9b160844fb3aea38caa4a5b96383f69a4
- Size of remote file:
- 343 MB
- SHA256:
- 81c1a790aaa3d39e90b66c3f04dbf47ef6facce136b899561cf03e70992c5443
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