Instructions to use ArturStepanenko/pythonV6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ArturStepanenko/pythonV6 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://ArturStepanenko/pythonV6") - Notebooks
- Google Colab
- Kaggle
Download pythonV6/saved_model.pb from ArturStepanenko/pythonV6: direct link, hf CLI and curl.
- Browser
- Download file 281 kB
-
https://huggingface.co/ArturStepanenko/pythonV6/resolve/c73a13dcc3faa5f20ad32f4708256b2cb37bc129/pythonV6/saved_model.pb
- Command line
-
hf download hf://ArturStepanenko/pythonV6@c73a13dcc3faa5f20ad32f4708256b2cb37bc129/pythonV6/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/ArturStepanenko/pythonV6/resolve/c73a13dcc3faa5f20ad32f4708256b2cb37bc129/pythonV6/saved_model.pb
281 kB
- Xet hash:
- b3409766ee0dccf4297d41030ec3e577cd9095600f4d5e21c4b1ecaa8967ac1e
- Size of remote file:
- 281 kB
- SHA256:
- 7739a5bf1d98d97afe6e937b74107b6b91520c7e4405224e103567ca0bacd5de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.