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:
# !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://danhtran2mind/En2Vi-Translation-Transformer-TensorFlow") - Notebooks
- Google Colab
- Kaggle
Rename saved_models/en_vi_translation.keras to ckpts/en_vi_translation.keras
Browse files
.gitattributes
CHANGED
|
@@ -38,3 +38,4 @@ dataset/train/train.vi filter=lfs diff=lfs merge=lfs -text
|
|
| 38 |
dataset_convert/train/train.en filter=lfs diff=lfs merge=lfs -text
|
| 39 |
dataset_convert/train/train.vi filter=lfs diff=lfs merge=lfs -text
|
| 40 |
saved_models/en_vi_translation.keras filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 38 |
dataset_convert/train/train.en filter=lfs diff=lfs merge=lfs -text
|
| 39 |
dataset_convert/train/train.vi filter=lfs diff=lfs merge=lfs -text
|
| 40 |
saved_models/en_vi_translation.keras filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
ckpts/en_vi_translation.keras filter=lfs diff=lfs merge=lfs -text
|
{saved_models → ckpts}/en_vi_translation.keras
RENAMED
|
File without changes
|