metadata
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
tags:
- TensorBlock
- GGUF
base_model: yentinglin/Taiwan-LLM-7B-v2.0-base
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
yentinglin/Taiwan-LLM-7B-v2.0-base - GGUF
This repo contains GGUF format model files for yentinglin/Taiwan-LLM-7B-v2.0-base.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.
Our projects
| Awesome MCP Servers | TensorBlock Studio |
|---|---|
 |
 |
| A comprehensive collection of Model Context Protocol (MCP) servers. | A lightweight, open, and extensible multi-LLM interaction studio. |
| 👀 See what we built 👀 | 👀 See what we built 👀 |
Prompt template
{system_prompt}</s>USER: {prompt}</s>ASSISTANT:
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Taiwan-LLM-7B-v2.0-base-Q2_K.gguf | Q2_K | 0.001 GB | smallest, significant quality loss - not recommended for most purposes |
| Taiwan-LLM-7B-v2.0-base-Q3_K_S.gguf | Q3_K_S | 0.001 GB | very small, high quality loss |
| Taiwan-LLM-7B-v2.0-base-Q3_K_M.gguf | Q3_K_M | 0.001 GB | very small, high quality loss |
| Taiwan-LLM-7B-v2.0-base-Q3_K_L.gguf | Q3_K_L | 0.001 GB | small, substantial quality loss |
| Taiwan-LLM-7B-v2.0-base-Q4_0.gguf | Q4_0 | 0.001 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Taiwan-LLM-7B-v2.0-base-Q4_K_S.gguf | Q4_K_S | 0.001 GB | small, greater quality loss |
| Taiwan-LLM-7B-v2.0-base-Q4_K_M.gguf | Q4_K_M | 0.001 GB | medium, balanced quality - recommended |
| Taiwan-LLM-7B-v2.0-base-Q5_0.gguf | Q5_0 | 0.001 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Taiwan-LLM-7B-v2.0-base-Q5_K_S.gguf | Q5_K_S | 0.001 GB | large, low quality loss - recommended |
| Taiwan-LLM-7B-v2.0-base-Q5_K_M.gguf | Q5_K_M | 0.001 GB | large, very low quality loss - recommended |
| Taiwan-LLM-7B-v2.0-base-Q6_K.gguf | Q6_K | 0.001 GB | very large, extremely low quality loss |
| Taiwan-LLM-7B-v2.0-base-Q8_0.gguf | Q8_0 | 0.001 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/yentinglin_Taiwan-LLM-7B-v2.0-base-GGUF --include "Taiwan-LLM-7B-v2.0-base-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/yentinglin_Taiwan-LLM-7B-v2.0-base-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'