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import os | |
import gradio as gr | |
from transformers import pipeline | |
# Get the Hugging Face API token from environment variables | |
api_token = os.getenv("HUGGINGFACE_API_TOKEN_V") | |
print('----------------',api_token,'-----------------') | |
# Check if the API token is set | |
if not api_token: | |
raise ValueError("API token is not set. Please set the HUGGINGFACE_API_TOKEN environment variable.") | |
# Initialize the text generation pipeline with authentication | |
pipe = pipeline("text-generation", model="meta-llama/Meta-Llama-3.1-405B", use_auth_token=True) | |
# Define the function to generate text | |
def generate_text(prompt): | |
result = pipe(prompt, max_length=50, num_return_sequences=1) | |
return result[0]['generated_text'] | |
# Create a Gradio interface | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."), | |
outputs="text", | |
title="Meta-Llama Text Generation", | |
description="Generate text using the Meta-Llama 3.1 405B model." | |
) | |
# Launch the interface | |
iface.launch() |