Create app.py

app.py

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+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+import torch
+import gradio as gr
+
+# Load the tokenizer and the model
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2-medium")
+model = GPT2LMHeadModel.from_pretrained("gpt2-medium")
+
+# Function for generating text
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs.input_ids, max_length=100, num_return_sequences=1)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Define a function that will be used in the Gradio interface
+def generate_from_prompt(prompt):
+    return generate_text(prompt)
+
+# Create the Gradio interface
+gr.Interface(fn=generate_from_prompt, inputs="text", outputs="text", title="GPT-2 Medium Text Generator").launch()