Instructions to use alexvmt/CBNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use alexvmt/CBNet 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://alexvmt/CBNet") - Notebooks
- Google Colab
- Kaggle
Download class_list.yaml from alexvmt/CBNet: direct link, hf CLI and curl.
- Browser
- Download file 304 Bytes
-
https://huggingface.co/alexvmt/CBNet/resolve/main/class_list.yaml
- Command line
-
hf download hf://alexvmt/CBNet/class_list.yaml
-
curl -L -o class_list.yaml https://huggingface.co/alexvmt/CBNet/resolve/main/class_list.yaml
304 Bytes
| '1': atherurus_africanus | |
| '10': philantomba_monticola | |
| '11': potamochoerus_porcus | |
| '12': tragelaphus_spekii | |
| '2': cephalophus_callipygus | |
| '3': cephalophus_dorsalis | |
| '4': cephalophus_silvicultor | |
| '5': cercocebus_torquatus | |
| '6': cricetomys_emini | |
| '7': loxodonta_cyclotis | |
| '8': mandrillus_sphinx | |
| '9': pan_troglodytes | |