app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, TextGenerationPipeline

# Load the model and tokenizer
model = AutoModelForCausalLM.from_pretrained('cbauer/groupchatGPT', trust_remote_code=True, ignore_mismatched_sizes=True)
tokenizer = AutoTokenizer.from_pretrained('cbauer/groupchatGPT')

# Initialize the Text Generation pipeline
generator = TextGenerationPipeline(model=model, tokenizer=tokenizer)

def generate(text):
    result = generator(text, max_length=30, num_return_sequences=1)
    return result[0]["generated_text"]

examples = [
    ["###Chase Hello"],
    ["### Jake Whats up"],
]

demo = gr.Interface(
    fn=generate,
    inputs=gr.components.Textbox(lines=5, label="Input Text"),
    outputs=gr.components.Textbox(label="Generated Text"),
    examples=examples
)

demo.launch()