Create app.py

app.py

@@ -0,0 +1,36 @@
+import torch
+import gradio as gr
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+# Load pre-trained model and tokenizer
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
+
+# Define a function to generate text
+def generate_text(input_text):
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+
+    # Generate text
+    with torch.no_grad():
+        output = model.generate(input_ids, max_length=100, no_repeat_ngram_size=True, do_sample=True, temperature=0.9)
+    
+    # Decode the generated text
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    
+    return generated_text
+
+# Create a Gradio interface
+
+# Create a Gradio interface
+iface = gr.Interface(
+    generate_text,
+    gr.Textbox(lines=5, label="Input Text"),
+    "textbox",
+    examples=[
+        ["Once upon a time, in a land far, far away..."]
+    ],
+    title="GPT-2 Text Generation",
+    description="Enter some text and GPT-2 will generate more!",
+    theme="compact"
+)
+iface.launch()