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_5/scheduler.pt from Sag1012/machine-translation: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/Sag1012/machine-translation/resolve/main/EncoderDecoder_5/scheduler.pt
- Command line
-
hf download hf://Sag1012/machine-translation/EncoderDecoder_5/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/Sag1012/machine-translation/resolve/main/EncoderDecoder_5/scheduler.pt
1.06 kB
- Xet hash:
- 219a29c63bb5485989998ccf8ae3eaf8e02d846677325663765a858f95d088d3
- Size of remote file:
- 1.06 kB
- SHA256:
- 466d9678b88de86639a0a0f85f8525b3f815a8068c10fc9b45ced453b6a8153c
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