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import torch | |
import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
MODEL_NAME = 'meta-llama/Llama-2-7b-chat-hf' | |
ADAPTERS_NAME = 'pivovalera2012/Llama-2-7b-Dr-Hous-test' | |
model_trained = AutoModelForCausalLM.from_pretrained( | |
MODEL_NAME, | |
device_map=device_map, | |
trust_remote_code=True, | |
quantization_config=bnb_config, | |
) | |
model_trained = PeftModel.from_pretrained(model_trained, ADAPTERS_NAME) | |
model_trained = model_trained.merge_and_unload() | |
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) | |
def generate_text(prompt): | |
return 'Привет' | |
demo = gr.Interface( | |
generate_text, | |
inputs=["textbox"], | |
outputs=["textbox"] | |
) | |
demo.launch() |