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()