import gradio as gr import torch from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline from diffusers import StableDiffusionPipeline from huggingface_hub import login import os from PIL import Image import io login(token=os.environ["HF_TOKEN"]) model_id = "mistralai/Mistral-7B-Instruct-v0.1" # Requiere acceso tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=True) model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.float16, use_auth_token=True) pipe = pipeline("text-generation", model=model, tokenizer=tokenizer) def chat(user_input): prompt = f"""[INST] {user_input.strip()} [/INST]""" output = pipe(prompt, max_new_tokens=200, temperature=0.7, do_sample=True)[0]["generated_text"] response = output.split("[/INST]")[-1].strip() return response gr.Interface(fn=chat, inputs="text", outputs="text", title="MyBot - Texto").launch()