Instructions to use Radventure/fire_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Radventure/fire_detection with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Radventure/fire_detection") - Notebooks
- Google Colab
- Kaggle
Download final_model.keras from Radventure/fire_detection: direct link, hf CLI and curl.
- Browser
- Download file 282 MB
-
https://huggingface.co/Radventure/fire_detection/resolve/main/final_model.keras
- Command line
-
hf download hf://Radventure/fire_detection/final_model.keras
-
curl -L -o final_model.keras https://huggingface.co/Radventure/fire_detection/resolve/main/final_model.keras
282 MB
- Xet hash:
- f91b427f5fa441710424d1fb5f876ec8ddc02866e8486185b46fb2f22fa89fc0
- Size of remote file:
- 282 MB
- SHA256:
- cf2030a395e2bf6d9a0693a5866057d20dca1329a45b1a512174474b84f6ccf3
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