Create app.py

app.py

@@ -0,0 +1,36 @@
+import numpy as np
+import os
+import gradio as gr
+
+os.environ["WANDB_DISABLED"] = "true"
+
+from datasets import load_dataset, load_metric
+from transformers import (
+    AutoConfig,
+    # AutoModelForSequenceClassification,
+    AutoTokenizer,
+    TrainingArguments,
+    logging,
+pipeline
+)
+
+
+analyzer = pipeline(
+    "sentiment-analysis", model="FFZG-cleopatra/M2SA-text-only"
+)
+
+def predict_sentiment(x):
+    print(label2id[analyzer(x))
+    return label2id[analyzer(x)[0]["label"]]
+
+
+interface = gr.Interface(
+    fn=predict_sentiment,
+    inputs='text',
+    outputs=['text'],
+    title='Multilingual-Multimodal-Sentiment-Analysis',
+    examples= ["I love tea","I hate coffee"],
+    description='Get the positive/neutral/negative sentiment for the given input.'
+)
+
+interface.launch(inline = False)