ELYZA Japanese Llama 2 13b Instruct

🚀 ELYZA-japanese-Llama-2-13b

ELYZA-japanese-Llama-2-13b 是基於 Llama 2 進行額外預訓練以增強日語能力的模型。詳細信息請參考 博客文章。

🚀 快速開始

模型描述

ELYZA-japanese-Llama-2-13b 是以 Llama 2 為基礎，為擴展日語能力而進行額外預訓練的模型。詳細內容可參考 Blog文章。

💻 使用示例

基礎用法

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

B_INST, E_INST = "[INST]", "[/INST]"
B_SYS, E_SYS = "<<SYS>>\n", "\n<</SYS>>\n\n"
DEFAULT_SYSTEM_PROMPT = "あなたは誠実で優秀な日本人のアシスタントです。"
text = "仕事の熱意を取り戻すためのアイデアを5つ挙げてください。"

model_name = "elyza/ELYZA-japanese-Llama-2-13b-instruct"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.bfloat16,
    use_cache=True,
    device_map="auto",
    low_cpu_mem_usage=True,
)
model.eval()

prompt = "{bos_token}{b_inst} {system}{prompt} {e_inst} ".format(
    bos_token=tokenizer.bos_token,
    b_inst=B_INST,
    system=f"{B_SYS}{DEFAULT_SYSTEM_PROMPT}{E_SYS}",
    prompt=text,
    e_inst=E_INST,
)
token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")

with torch.no_grad():
    output_ids = model.generate(
        token_ids.to(model.device),
        max_new_tokens=256,
        pad_token_id=tokenizer.pad_token_id,
        eos_token_id=tokenizer.eos_token_id,
    )
output = tokenizer.decode(output_ids.tolist()[0][token_ids.size(1) :], skip_special_tokens=True)
print(output)

📚 詳細文檔

ELYZA-japanese-Llama-2-13b 模型

👨‍💻 開發者

以下按字母順序排列：

• Akira Sasaki
• Masato Hirakawa
• Shintaro Horie
• Tomoaki Nakamura
• Sam Passaglia
• Daisuke Oba（實習生）

📄 許可證

Llama 2 遵循 LLAMA 2 社區許可證，版權所有 (c) Meta Platforms, Inc. 保留所有權利。

📖 引用方式

@misc{elyzallama2023, 
      title={ELYZA-japanese-Llama-2-13b}, 
      url={https://huggingface.co/elyza/ELYZA-japanese-Llama-2-13b}, 
      author={Akira Sasaki and Masato Hirakawa and Shintaro Horie and Tomoaki Nakamura and Sam Passaglia and Daisuke Oba},
      year={2023},
}

🔗 參考文獻

@misc{touvron2023llama,
      title={Llama 2: Open Foundation and Fine-Tuned Chat Models}, 
      author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
      year={2023},
      eprint={2307.09288},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}