Taiwan LLM 7B V2.0.1 Chat GGUF

🚀 Taiwan LLM 7B v2.0.1 chat

Taiwan LLM is an advanced language model tailored for Traditional Chinese, focusing on the linguistic and cultural contexts of Taiwan.

🌟 Checkout Taiwan-LLM Demo Chat-UI 🌟

🚀 Quick Start

Taiwan LLM is an advanced language model tailored for Traditional Chinese, focusing on the linguistic and cultural contexts of Taiwan. Developed from a large base model, it's enriched with diverse Taiwanese textual sources and refined through Supervised Fine-Tuning. This model excels in language understanding and generation, aligning closely with Taiwan's cultural nuances. It demonstrates improved performance on various benchmarks like TC-Eval, showcasing its contextual comprehension and cultural relevance. For detailed insights into Taiwan LLM's development and features, refer to our technical report.

✨ Features

• Tailored for Traditional Chinese, focusing on Taiwan's linguistic and cultural contexts.
• Developed from a large base model, enriched with diverse Taiwanese textual sources.
• Refined through Supervised Fine-Tuning, excelling in language understanding and generation.
• Demonstrates improved performance on benchmarks like TC-Eval.

📦 Installation

To use the model, you need to install the necessary libraries:

pip install transformers>=4.34
pip install accelerate

💻 Usage Examples

Basic Usage

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-7B-v2.0.1-chat", 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"])

📚 Documentation

Model description

• Model type: A 7B parameter GPT-like 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-7B-v2.0-base

Model Sources

• Repository: https://github.com/MiuLab/Taiwan-LLaMa
• Demo: https://twllm.com/

Performance

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 5.0

🔧 Technical Details

For detailed insights into Taiwan LLM's development and features, refer to our technical report.

📄 License

This model is licensed under the Apache-2.0 license.

📚 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}
}