| import gradio as gr | |
| import torch | |
| import json | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| tokenizer = AutoTokenizer.from_pretrained("keminglu/pivoine-7b", use_auth_token="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", padding_side="left") | |
| model = AutoModelForCausalLM.from_pretrained("keminglu/pivoine-7b", use_auth_token="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", torch_dtype=torch.float16) | |
| #input_device = torch.device("cuda:5") | |
| model.requires_grad_(False) | |
| model.eval() | |
| #model = model.to(input_device) | |
| # examples = json.load(open("examples.json")) |