Instructions to use rcodina/tm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use rcodina/tm2 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://rcodina/tm2") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from rcodina/tm2: direct link, hf CLI and curl.
- Browser
- Download file 5.25 MB
-
https://huggingface.co/rcodina/tm2/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://rcodina/tm2@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/rcodina/tm2/resolve/refs%2Fpr%2F1/saved_model.pb
5.25 MB
- Xet hash:
- fc186c7df57195386dc9a0a974af45bad471c1450c9b081c6efeb2877a5aad8c
- Size of remote file:
- 5.25 MB
- SHA256:
- b19fa21d876fc4e22a6d8a3904a82ebea192c7d9400693ba9361f72f6eed7e87
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