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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() |