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_2/generation_config.json from Sag1012/machine-translation: direct link, hf CLI and curl.
- Browser
- Download file 161 Bytes
-
https://huggingface.co/Sag1012/machine-translation/resolve/main/EncoderDecoder_2/generation_config.json
- Command line
-
hf download hf://Sag1012/machine-translation/EncoderDecoder_2/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Sag1012/machine-translation/resolve/main/EncoderDecoder_2/generation_config.json
161 Bytes
| { | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 2, | |
| "eos_token_id": 2, | |
| "forced_eos_token_id": 2, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.46.3" | |
| } | |