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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() |