This model is intended for chat and assistant tasks in Vietnamese. It can be used to answer general questions, assist in writing, and provide information in Vietnamese.

Out-of-Scope Use

The model should not be used for generating harmful, illegal, or unethical content. It is not suitable for high-stakes medical or legal advice.

Training Details

Training Data

The model was fine-tuned on the 5CD-AI/Vietnamese-alpaca-gpt4-gg-translated dataset, which contains 500 samples of instruction-following data in Vietnamese.

Training Procedure

Framework: MLX
Iterations: 50 (experimented with multiple ranks)
Batch Size: 1
Learning Rate: 2e-5
Hardware: Apple M2 Pro (16GB RAM)

Training Hyperparameters

LoRA Rank: 16 (Optimal)
LoRA Alpha: 32
Max Sequence Length: 256

Evaluation

Results

Based on local evaluation on a test set:

Test Loss: 1.7527
Perplexity: 5.7702

How to Get Started with the Model

To generate text using this adapter with mlx-vlm:

bash

python -m mlx_vlm.generate \
  --model-path mlx-community/Qwen3.5-0.8B-4bit \
  --adapter-path baeGil/Qwen3.5-0.8B-mlx-LoRA \
  --prompt "### Instruction:\nCách nấu phở bò truyền thống?\n\n### Response:\n" \
  --max-tokens 256

Environmental Impact

Hardware Type: Apple M2 Pro
Time used: ~12 minutes
Carbon Emitted: Negligible due to high efficiency of Apple Silicon.

Model Card Contact

[baeGil]

Github Repository

2A202600038-DoHaiNam-Day21