tujia-llm

LoRA weights and evaluation for Tujia language generation. First public release: v0.2 (research preview). v0.1 was internal only.

Status: research preview. Suitable for draft lookup and short-sentence translation, not for authoritative output. Exact word-lookup accuracy is 5.8%; sentence similarity is 0.45. See evaluation for details.

Model

Download

Install

Requirements: macOS 13+, Apple Silicon, Python 3.10+.

pip install tujia-llm                          # after the PyPI release
pip install dist/tujia_llm-0.2.0-py3-none-any.whl   # offline / local wheel

The wheel contains code only. Weights (74 MB) and the base model are downloaded on first run.

CLI

tujia-llm info                                  # backend, precision, memory
tujia-llm lookup 酒
tujia-llm translate "大家都过好日子。"
tujia-llm translate "大家都过好日子，土家人们都相好。" --split
tujia-llm translate "zɤ³⁵" --to zh
tujia-llm translate "zɤ³⁵" --to en

Options: --adapter (local directory or HF repo id), --precision auto|bf16|4bit, --max-tokens, --json.

tujia-llm lookup 酒 --adapter /path/to/adapter-dir --json

For development, python scripts/infer.py offers the same prompts without installation.

Windows / CPU (GGUF)

The MLX build is Apple Silicon only. For Windows, Linux, and Intel Macs use the GGUF build with llama.cpp or Ollama — see docs/windows-gguf.md.

ollama create tujia -f gguf/Modelfile
ollama run tujia "「酒」用土家语怎么说？"

Capabilities and limits

Works

• Chinese word → Tujia form + IPA (reliable for high-frequency words)
• Chinese short sentence → Tujia sentence (stable up to roughly 8 syllables)
• Tujia sentence → English

Does not work

• Authoritative translation, publication-grade text, legal or medical use
• Folk songs, ritual language, and other low-resource registers
• Southern Tujia (Luxi) and non-Longshan varieties such as Baojing
• Out-of-vocabulary words: there is no refusal mechanism, so the model will invent forms

Evaluation summary

* Base model evaluated on the first 100 items only, so not directly comparable to the full sets.

Full tables, dialect breakdowns, and failure modes: docs/eval-v0.2.md.

Prompt format

The model was trained on four fixed templates. Keep them unchanged at inference time:

「{Chinese word}」用土家语怎么说？
把这句话翻译成土家语：{Chinese sentence}
把这句话翻译成汉语：{Tujia sentence}
把这句话翻译成英语：{Tujia sentence}

Output uses mixed Ye pinyin / IPA notation with superscript tone digits, e.g. zɤ³⁵.

Layout

scripts/infer.py        inference example
docs/eval-v0.2.md       evaluation report
release/                release config and upload script
MODEL_CARD.md           model card
NOTICE                  usage boundaries

Citation

@misc{tujia-llm-v0.1,
  title  = {tujia-llm: LoRA adapter for Tujia language generation (v0.2)},
  author = {ibaibing},
  year   = {2026},
  note   = {Research preview}
}