app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Model name from Hugging Face
model_name = "segolilylabs/Lily-Cybersecurity-7B-v0.2"

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

def generate_text(input_text):
    # Tokenize the input text
    inputs = tokenizer(input_text, return_tensors="pt")
    
    # Generate output from the model
    outputs = model.generate(**inputs, max_length=100)
    
    # Decode the output tokens back into text
    output_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    
    return output_text

# Create a Gradio interface
demo = gr.Interface(fn=generate_text, inputs="text", outputs="text")

# Launch the app
demo.launch()