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
File size: 528 Bytes
ee03b1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | 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
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