Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load model and tokenizer directly from Hugging Face Hub
+model = AutoModelForCausalLM.from_pretrained("Manasa1/gpt-finetuned-tweets")
+tokenizer = AutoTokenizer.from_pretrained("Manasa1/gpt-finetuned-tweets")
+
+
+# Define the function to generate tweets
+def generate_tweet():
+    prompt = "Generate a tweet that reflects the personality in the fine-tuned dataset:"
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_length=280,
+        num_return_sequences=1,
+        top_p=0.9,
+        temperature=0.7
+    )
+    generated_tweet = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return generated_tweet.strip()
+
+# Gradio Interface
+with gr.Blocks() as app:
+    gr.Markdown("# AI Tweet Generator")
+    gr.Markdown("Click the button below to generate a tweet reflecting the fine-tuned personality.")
+    generate_button = gr.Button("Generate")
+    output_box = gr.Textbox(label="Generated Tweet")
+    
+    generate_button.click(generate_tweet, inputs=None, outputs=output_box)
+
+# Launch the app locally
+app.launch()