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| from tamilatis.predict import TamilATISPredictor | |
| from tamilatis.model import JointATISModel | |
| import numpy as np | |
| from sklearn.preprocessing import LabelEncoder | |
| import gradio as gr | |
| model_name = "microsoft/xlm-align-base" | |
| tokenizer_name = "microsoft/xlm-align-base" | |
| num_labels = 78 | |
| num_intents = 23 | |
| checkpoint_path = "models/xlm_align_base.bin" | |
| intent_encoder_path = "models/intent_classes.npy" | |
| ner_encoder_path = "models/ner_classes.npy" | |
| def predict_function(text): | |
| label_encoder = LabelEncoder() | |
| label_encoder.classes_ = np.load(ner_encoder_path) | |
| intent_encoder = LabelEncoder() | |
| intent_encoder.classes_ = np.load(intent_encoder_path) | |
| model = JointATISModel(model_name,num_labels,num_intents) | |
| predictor = TamilATISPredictor(model,checkpoint_path,tokenizer_name, | |
| label_encoder,intent_encoder,num_labels) | |
| slot_prediction, intent_preds = predictor.get_predictions(text) | |
| return slot_prediction, intent_preds | |
| title = "MultiTask Learning in Intent Detection and Slot Prediction for Tamil Conversational Dialogues using Multilingual Pretrained Models" | |
| article="This is a demo for the MultiTask model trained on Tamil Translated conversations from ATIS dataset. The code can be found [here](https://github.com/seanbenhur/tamilatis). Made with ❤ by [Sean Benhur](https://www.linkedin.com/in/seanbenhur/)" | |
| examples = ["ஹைதராபாத்தில் இருந்து உதய்பூர் செல்லும் விமானங்களைக் காட்டு", "எனக்கு டெல்லியில் இருந்து சென்னைக்கு விமானம் வேண்டும்"] | |
| intent_output = gr.outputs.Textbox(type="auto",label="Intent") | |
| slots_output = gr.outputs.Textbox(type="auto",label="Slots") | |
| iface = gr.Interface(fn=predict_function,article=article, inputs="text", title=title,outputs=[intent_output,slots_output], | |
| examples=examples) | |
| iface.launch() | |