Instructions to use Pogonyalov47/model47 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Pogonyalov47/model47 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://Pogonyalov47/model47") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from Pogonyalov47/model47: direct link, hf CLI and curl.
- Browser
- Download file 128 kB
-
https://huggingface.co/Pogonyalov47/model47/resolve/main/saved_model.pb
- Command line
-
hf download hf://Pogonyalov47/model47/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/Pogonyalov47/model47/resolve/main/saved_model.pb
128 kB
- Xet hash:
- ab3de5db7a65473aa2f59e7007ded7c7a8c83dfab1e6f4e590ba0c1debba1058
- Size of remote file:
- 128 kB
- SHA256:
- 49610749afad21f503cabc986ffcde29b5fbe28d0a2a6f92f65e8e38af1ab725
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.