Instructions to use Sag1012/machine-translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Sag1012/machine-translation 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://Sag1012/machine-translation") - Notebooks
- Google Colab
- Kaggle
Download Summarization/optimizer.pt from Sag1012/machine-translation: direct link, hf CLI and curl.
- Browser
- Download file 484 MB
-
https://huggingface.co/Sag1012/machine-translation/resolve/main/Summarization/optimizer.pt
- Command line
-
hf download hf://Sag1012/machine-translation/Summarization/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Sag1012/machine-translation/resolve/main/Summarization/optimizer.pt
484 MB
- Xet hash:
- 70e4feb5ef33d268362c3885c34b070f538662cc5f63754b670cb20830b28314
- Size of remote file:
- 484 MB
- SHA256:
- d43bb81c11ff1abcd96cc03bcb1fd4c078a42b0d01a378025cc5021b98a6aa8d
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