CodeSagePath/Mistral_Model_Test_1

1import gradio as gr2import os3from transformers import AutoTokenizer, AutoModelForCausalLM4from huggingface_hub import login5import torch6import tensorflow as tf7import flax8 9 10# Access the secret token from environment variables11hf_token = os.getenv('HF_TOKEN')12 13# Authenticate using the Hugging Face token14login(hf_token)15 16# Load model and tokenizer17tokenizer = AutoTokenizer.from_pretrained("mistralai/Mixtral-8x7B-v0.1", use_auth_token=True)18model = AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B-v0.1", use_auth_token=True)19 20def generate_response(question):21    inputs = tokenizer.encode(question, return_tensors="pt")22    outputs = model.generate(inputs, max_length=50)23    return tokenizer.decode(outputs[0], skip_special_tokens=True)24 25# Create Gradio interface26iface = gr.Interface(fn=generate_response, inputs="text", outputs="text")27iface.launch()28