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 EncoderDecoder_3/training_args.bin from Sag1012/machine-translation: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Sag1012/machine-translation/resolve/main/EncoderDecoder_3/training_args.bin
- Command line
-
hf download hf://Sag1012/machine-translation/EncoderDecoder_3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sag1012/machine-translation/resolve/main/EncoderDecoder_3/training_args.bin
5.37 kB
- Xet hash:
- a546dc62821859361ef11c8b05f89d9490735181af4bf75e262c31bb2ba2deb0
- Size of remote file:
- 5.37 kB
- SHA256:
- 73f16296db0ed34a2fc06867f280c290bb1db767db7e399585cc5d9e108d0438
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