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1import torch
2from transformers import LlamaForCausalLM, LlamaTokenizer
3from peft import PeftModel
4
5base_model = "decapoda-research/llama-7b-hf"
6# Please note that the special license of decapoda-research/llama-7b-hf is applied.
7model = LlamaForCausalLM.from_pretrained(base_model, torch_dtype=torch.float16)
8tokenizer = LlamaTokenizer.from_pretrained(base_model)
9model = PeftModel.from_pretrained(
10 model,
11 "izumi-lab/llama-7b-japanese-lora-v0",
12 torch_dtype=torch.float16,
13)@preprint{Suzuki2023-llmj,
title={{日本語インストラクションデータを用いた対話可能な日本語大規模言語モデルのLoRAチューニング}},
author={鈴木 雅弘 and 平野 正徳 and 坂地 泰紀},
doi={10.51094/jxiv.422},
archivePrefix={Jxiv},
year={2023}
}