app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("databricks/dolly-v2-3b")
model = AutoModelForCausalLM.from_pretrained("databricks/dolly-v2-3b")

def generate_text(prompt):
    # Tokenize the input prompt
    inputs = tokenizer.encode(prompt, return_tensors="pt")

    # Generate text based on the prompt
    output = model.generate(inputs, max_length=100, num_return_sequences=1)

    # Decode the generated output
    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)

    return generated_text

# Define the Gradio interface
iface = gr.Interface(
    fn=generate_text,
    inputs="text",
    outputs="text",
    title="Transformer Text Generation",
    description="Enter a prompt and the model will generate text based on it.",
)

# Launch the Gradio interface
iface.launch()