---
license: apache-2.0
language:
- en
library_name: mlx
pipeline_tag: text-generation
base_model: Qwen/Qwen3-1.7B
base_model_relation: finetune
datasets:
- jokernifty/docs-instruct-nextjs-20260601-0306
tags:
- mlx
- qwen2
- instruction-tuning
- downftuner
- synthetic-data
---

# qwen3-1.7b-docs-20260601-0306

LoRA fine-tune of [`Qwen/Qwen3-1.7B`](https://huggingface.co/Qwen/Qwen3-1.7B)
on a freshly-synthesized mixed-Wikipedia instruction dataset.

- **Training**: MLX-LM LoRA, 800 iterations, 16 layers, LR 1.0e-5.
- **Dataset**: [jokernifty/docs-instruct-nextjs-20260601-0306](https://huggingface.co/datasets/jokernifty/docs-instruct-nextjs-20260601-0306)
- **Pipeline**: [DownFTuner](https://github.com/jokernifty/downftuner)

## Usage

```python
from mlx_lm import load, generate
model, tokenizer = load("jokernifty/qwen3-1.7b-docs-nextjs-20260601-0306")
print(generate(model, tokenizer, prompt="Explain the Krebs cycle.", max_tokens=200))
```

For `transformers`, convert from MLX format with `mlx_lm.convert --hf-path jokernifty/qwen3-1.7b-docs-nextjs-20260601-0306` or load via `mlx_lm`.