Instructions to use shrusti333/language_translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use shrusti333/language_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://shrusti333/language_translation") - Notebooks
- Google Colab
- Kaggle
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Download README.md from shrusti333/language_translation: direct link, hf CLI and curl.
- Browser
- Download file 131 Bytes
-
https://huggingface.co/shrusti333/language_translation/resolve/main/README.md
- Command line
-
hf download hf://shrusti333/language_translation/README.md
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curl -L -o README.md https://huggingface.co/shrusti333/language_translation/resolve/main/README.md
131 Bytes
metadata
datasets:
- shrusti333/konkani_translation
language:
- en
metrics:
- accuracy
pipeline_tag: translation
library_name: keras