Instructions to use danhtran2mind/En2Vi-Translation-Transformer-TensorFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use danhtran2mind/En2Vi-Translation-Transformer-TensorFlow with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://danhtran2mind/En2Vi-Translation-Transformer-TensorFlow") - Notebooks
- Google Colab
- Kaggle
| import pickle | |
| import tensorflow as tf | |
| def load_tokenizers(en_path='tokenizers/en_tokenizer.pkl', | |
| vi_path='tokenizers/vi_tokenizer.pkl'): | |
| with open(en_path, 'rb') as f: | |
| en_tokenizer = pickle.load(f) | |
| with open(vi_path, 'rb') as f: | |
| vi_tokenizer = pickle.load(f) | |
| en_tokenizer = tf.keras.preprocessing.text.tokenizer_from_json(en_tokenizer) | |
| vi_tokenizer = tf.keras.preprocessing.text.tokenizer_from_json(vi_tokenizer) | |
| return en_tokenizer, vi_tokenizer | |