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Model Card for Taiwan LLM 8x7B-DPO
Taiwan LLM is an advanced language model tailored for Traditional Chinese, focusing on the linguistic and cultural contexts of Taiwan.
Model description
- Model type: A 8x7B parameter Mixtral MoE model fine-tuned on a mix of publicly available, synthetic datasets.
- Language(s) (NLP): Primarily Traditional Chinese (zh-tw)
- Finetuned from model: yentinglin/Taiwan-LLM-MoE-alpha
Model Sources
- Repository: https://github.com/MiuLab/Taiwan-LLaMa
- Demo: https://twllm.com/
Performance
Checkout leaderboard in Tw Chatbot Arena
TMMLUS+ score:
- yentinglin/Taiwan-LLM-MoE-alpha: 43.93
- yentinglin/Taiwan-LLM-8x7B-DPO: TBD
Intended uses
Here's how you can run the model using the pipeline()
function from 🤗 Transformers:
# pip install transformers>=4.34
# pip install accelerate
import torch
from transformers import pipeline
pipe = pipeline("text-generation", model="yentinglin/Taiwan-LLM-8x7B-DPO", torch_dtype=torch.bfloat16, device_map="auto")
# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
messages = [
{
"role": "system",
"content": "你是一個人工智慧助理",
},
{"role": "user", "content": "東北季風如何影響台灣氣候?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Citation
If you find Taiwan LLM useful in your work, please cite it with:
@misc{lin2023taiwan,
title={Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model},
author={Yen-Ting Lin and Yun-Nung Chen},
year={2023},
eprint={2311.17487},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Acknowledgement
Ubitus provides valuable compute resources for the project.
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