Update app.py

app.py

@@ -7,35 +7,36 @@ import json
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Replace 'username/your_model_name' with your Hugging Face model name
-model_name = "Manasa1/your_model_name"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+model_dir = "Manasa1/your_model_name"
+fine_tuned_model = GPT2LMHeadModel.from_pretrained(model_dir)
+fine_tuned_tokenizer = GPT2Tokenizer.from_pretrained(model_dir)
 
+
+# Create a text-generation pipeline
+generator = pipeline('text-generation', model=fine_tuned_model, tokenizer=fine_tuned_tokenizer)
+
+# Function to generate tweets
 def generate_tweet(prompt):
-    # Tokenize the input
-    inputs = tokenizer(prompt, return_tensors="pt")
-    
-    # Generate text using the model
-    outputs = model.generate(
-        inputs["input_ids"], 
-        max_length=280,  # Limit tweets to 280 characters
-        num_return_sequences=1,  # Number of tweets to generate
-        top_k=50,  # Sampling from top k tokens
-        top_p=0.95,  # Sampling from top p cumulative probability
-        temperature=0.7,  # Adjust creativity
-        do_sample=True,  # Enable sampling
+    input_prompt = f"{prompt}\n\nTweet:"  # Format input for clarity
+    output = generator(
+        input_prompt,
+        max_length=50,  # Limit the total length of the generated text
+        num_return_sequences=1,
+        temperature=0.7,  # Control creativity
+        top_p=0.9,  # Use nucleus sampling
+        pad_token_id=fine_tuned_tokenizer.eos_token_id,  # Avoid padding issues
     )
-    
-    # Decode the generated text
-    tweet = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return tweet
+    # Extract the generated text and remove the input prompt from the output
+    generated_tweet = output[0]['generated_text'].replace(input_prompt, "").strip()
+    return generated_tweet
 
+# Gradio Interface
 interface = gr.Interface(
-    fn=generate_tweet,  # The function to call
-    inputs="text",      # User input is a single text box
-    outputs="text",     # Output is text
+    fn=generate_tweet,
+    inputs=gr.inputs.Textbox(label="Prompt", placeholder="Enter a topic for the tweet (e.g., AI, technology)"),
+    outputs=gr.outputs.Textbox(label="Generated Tweet"),
     title="AI Tweet Generator",
-    description="Enter a topic or a few words, and the AI will generate a creative tweet!"
+    description="Enter a topic or phrase, and the AI will generate a creative tweet. Powered by a fine-tuned GPT-2 model."
 )
 
 # Launch the app