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| import os | |
| import gradio as gr | |
| import tensorflow as tf | |
| import tensorflow_text as tf_text | |
| from huggingface_hub import Repository | |
| repo = Repository( | |
| local_dir="nmt-transformer", | |
| clone_from="pyimagesearch/nmt-transformer", | |
| use_auth_token=os.environ.get("token") | |
| ) | |
| reloaded = tf.saved_model.load("nmt-transformer/translator") | |
| title="Neural Machine Translation with Transformer" | |
| description="The model used here is a POC and not SOTA on NMT." | |
| examples=["how are you?", "good morning.", "how is your health?"] | |
| def get_translation(sentence): | |
| result = reloaded( | |
| sentence=tf.constant(sentence) | |
| ).numpy()[0].decode() | |
| return result | |
| nmt_space = gr.Interface( | |
| fn=get_translation, | |
| inputs=gr.Textbox(label="English Sentence"), | |
| outputs=gr.Textbox(label="French Sentence"), | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| ) | |
| nmt_space.launch() |