---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
license: apache-2.0
language:
  - zh
widget:
  - text: >-
      A chat between a curious user and an artificial intelligence assistant.
      The assistant gives helpful, detailed, and polite answers to the user's
      questions. USER: 你好，請問你可以幫我寫一封推薦信嗎？ ASSISTANT:
library_name: transformers
pipeline_tag: text-generation
extra_gated_heading: Acknowledge license to accept the repository.
extra_gated_prompt: Please contact the author for access.
extra_gated_button_content: Acknowledge license 同意以上內容
extra_gated_fields:
  Name: text
  Mail: text
  Organization: text
  Country: text
  Any utilization of the Taiwan LLM repository mandates the explicit acknowledgment and attribution to the original author: checkbox
  使用Taiwan LLM必須明確地承認和歸功於優必達株式會社 Ubitus 以及原始作者: checkbox
---

## Taiwan-LLM-13B-v2.0-chat with ExLlamaV2 Quantization
Original model 原始模型: https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat

This is a quantizated model from [yentinglin/Taiwan-LLM-13B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat) in exl2 format.

You are currently at the [main](https://huggingface.co/kennylam/Taiwan-LLM-13B-v2.0-chat-exl2/tree/main) branch, which provides only [measurement.json](measurement.json) used in the ExLlamaV2 quantization. Please take a look of your choices in following table of branches.

這裡是main branch, 只提供EvLlamaV2量化時所用到的[measurement.json](measurement.json)檔案。

[8.0bpw-h8](/kennylam/Taiwan-LLM-13B-v2.0-chat-exl2/tree/8.0bpw-h8) 8 bits per weight.

[6.0bpw-h6](/kennylam/Taiwan-LLM-13B-v2.0-chat-exl2/tree/6.0bpw-h6) 6 bits per weight.

[4.0bpw-h6](/kennylam/Taiwan-LLM-13B-v2.0-chat-exl2/tree/4.0bpw-h6) 4 bits per weight.

[3.0bpw-h6](/kennylam/Taiwan-LLM-13B-v2.0-chat-exl2/tree/3.0bpw-h6) 3 bits per weight.

[2.0bpw-h6](/kennylam/Taiwan-LLM-13B-v2.0-chat-exl2/tree/2.0bpw-h6) 2 bits per weight.

## Citation

If you find Taiwan LLM is 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

Taiwan LLM v2 is conducted in collaboration with [Ubitus K.K.](http://ubitus.net). Ubitus provides valuable compute resources for the project.