add code

app.py.txt

@@ -0,0 +1,34 @@
+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 = "/content/tamil_atis/xlm_align_base.bin"
+intent_encoder_path = "/content/tamil_atis/intent_annotations.npy"
+ner_encoder_path = "/content/tamil_atis/ner_annotations.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 = "Tamil ATIS"  
+iface = gr.Interface(fn=predict_function, inputs="text", title=title,theme="huggingface",outputs=["text","text"])
+iface.launch(share=True)
+

tamilatis

@@ -0,0 +1 @@
+Subproject commit b1022a9187d9d47c18b360fc45b7f55d3b40824f