Manasa1 commited on
Commit
6efad01
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1 Parent(s): 30480a5

Update app.py

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Files changed (1) hide show
  1. app.py +7 -4
app.py CHANGED
@@ -2,17 +2,18 @@ import gradio as gr
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  from transformers import GPT2LMHeadModel, GPT2Tokenizer, pipeline
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  # Replace 'username/your_model_name' with your Hugging Face model name
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- model_dir = "Manasa1/your_model_name"
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  fine_tuned_model = GPT2LMHeadModel.from_pretrained(model_dir)
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  fine_tuned_tokenizer = GPT2Tokenizer.from_pretrained(model_dir)
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-
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  # Create a text-generation pipeline
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  generator = pipeline('text-generation', model=fine_tuned_model, tokenizer=fine_tuned_tokenizer)
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  # Function to generate tweets
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  def generate_tweet(prompt):
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- input_prompt = f"{prompt}\n\nTweet:" # Format input for clarity
 
 
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  output = generator(
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  input_prompt,
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  max_length=150, # Limit the total length of the generated text
@@ -21,6 +22,7 @@ def generate_tweet(prompt):
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  top_p=0.9, # Use nucleus sampling
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  pad_token_id=fine_tuned_tokenizer.eos_token_id, # Avoid padding issues
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  )
 
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  # Extract the generated text and remove the input prompt from the output
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  generated_tweet = output[0]['generated_text'].replace(input_prompt, "").strip()
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  return generated_tweet
@@ -35,4 +37,5 @@ interface = gr.Interface(
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  )
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  # Launch the app
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- interface.launch()
 
 
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  from transformers import GPT2LMHeadModel, GPT2Tokenizer, pipeline
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  # Replace 'username/your_model_name' with your Hugging Face model name
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+ model_dir = "Manasa1/your_model_name" # Make sure to use your actual model path
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  fine_tuned_model = GPT2LMHeadModel.from_pretrained(model_dir)
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  fine_tuned_tokenizer = GPT2Tokenizer.from_pretrained(model_dir)
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  # Create a text-generation pipeline
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  generator = pipeline('text-generation', model=fine_tuned_model, tokenizer=fine_tuned_tokenizer)
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  # Function to generate tweets
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  def generate_tweet(prompt):
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+ # Updated input prompt to encourage creativity and engagement
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+ input_prompt = f"Write a creative and engaging tweet about {prompt}. Keep it concise and interesting, and include a call to action or a question for followers to engage with."
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+
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  output = generator(
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  input_prompt,
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  max_length=150, # Limit the total length of the generated text
 
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  top_p=0.9, # Use nucleus sampling
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  pad_token_id=fine_tuned_tokenizer.eos_token_id, # Avoid padding issues
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  )
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+
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  # Extract the generated text and remove the input prompt from the output
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  generated_tweet = output[0]['generated_text'].replace(input_prompt, "").strip()
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  return generated_tweet
 
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  )
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  # Launch the app
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+ interface.launch()
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+