Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoModel, AutoTokenizer
+import torch
+
+model_checkpoint = 'saideep-arikontham/twitter-roberta-base-sentiment-latest-trump-stance'
+model = AutoModelForSequenceClassification.from_pretrained(model_checkpoint, num_labels=2, ignore_mismatched_sizes=True)
+tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+
+def greet(text):
+    
+    model.to('mps')
+    inputs = tokenizer.encode(text, return_tensors="pt").to("mps")
+    # compute logits
+    logits = model(inputs).logits
+    # convert logits to label
+    predictions = torch.argmax(logits)
+
+    return "This text is " + id2label[predictions.tolist()] + "!!"
+
+
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo.launch()