Instructions to use ndgold/Qwen3-0.6B-EasyLanguage-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ndgold/Qwen3-0.6B-EasyLanguage-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3-0.6B-EasyLanguage-4bit ndgold/Qwen3-0.6B-EasyLanguage-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Qwen3-0.6B-EasyLanguage (4-bit, MLX)
LoRA fine-tune of Qwen/Qwen3-0.6B that rewrites live speech transcripts into easy-to-read registers across 20 language locales — German (Leichte Sprache), French (FALC), English (Easy/Plain English), Spanish (Lectura Fácil), Easy-to-Read Arabic (Inclusion Europe / Information for All), Letlæst (Inclusion Europe ETR), and more — for the Live Linguist on-device captioner. Each locale follows its own national / European Easy-to-Read or plain-language standard. Quantized to 4-bit for Apple-silicon inference via MLX.
It splits run-ons into short sentences, drops disfluencies, keeps names/numbers, and stays in the input language. Trained on a lean prompt (no few-shots) so the register is internalized — shorter prompts, lower live-caption latency.
Evaluation (held-out test set; SARI = simplification quality)
| lang | SARI ft | SARI stock | chrF ft | LID ft | compliance ft |
|---|---|---|---|---|---|
| de | 47.89 | 32.98 | 42.26 | 1.0 | 0.99 |
| fr | 56.93 | 33.31 | 51.19 | 1.0 | 1.0 |
| es | 59.34 | 36.57 | 54.79 | 1.0 | 0.995 |
| en | 59.17 | 32.46 | 54.57 | 1.0 | 1.0 |
| ar | 49.23 | 50.11 | 45.74 | 0.985 | 0.94 |
| da | 53.12 | 35.58 | 50.24 | 0.995 | 0.94 |
| et | 49.39 | 30.48 | 52.76 | 1.0 | 1.0 |
| fi | 50.55 | 35.2 | 56.33 | 1.0 | 0.985 |
| hi | 52.66 | 35.16 | 45.05 | 0.995 | 0.82 |
| it | 53.34 | 49.18 | 48.83 | 1.0 | 0.8299 |
| ja | 8.37 | 8.29 | 40.85 | 1.0 | 0.97 |
| ko | 49.55 | 43.77 | 40.03 | 1.0 | 0.98 |
| nl | 51.9 | 38.96 | 48.38 | 0.985 | 0.9 |
| pt-BR | 55.02 | 37.54 | 52.11 | 1.0 | 0.82 |
| pt-PT | 57.44 | 38.96 | 58.14 | 1.0 | 0.975 |
| ru | 50.61 | 41.13 | 49.65 | 1.0 | 0.94 |
| sk | 50.92 | 40.59 | 46.68 | 1.0 | 0.975 |
| sv | 53.23 | 40.16 | 55.08 | 0.995 | 0.96 |
| tr | 51.32 | 31.73 | 49.91 | 0.995 | 0.97 |
| vi | 59.62 | 41.3 | 58.75 | 1.0 | 0.725 |
| zh-CN | 8.75 | 8.5 | 51.67 | 0.955 | 0.925 |
Usage (MLX)
from mlx_lm import load, generate
model, tok = load("ndgold/Qwen3-0.6B-EasyLanguage-4bit")
msgs = [{"role":"system","content":"<framework system prompt>"},
{"role":"user","content":"Original: <utterance>\nRewritten:"}]
p = tok.apply_chat_template(msgs, add_generation_prompt=True, tokenize=False, enable_thinking=False)
print(generate(model, tok, prompt=p, max_tokens=96))
Sources & licenses
- Base model: Qwen3 (Apache-2.0).
- German seed data: tum-nlp/German4All-Corpus (German Wikipedia, CC BY-SA).
- Synthetic pairs (all other languages + de augmentation): spoken→easy-language pairs generated by Claude (Anthropic) — Leichte Sprache (de), FALC (fr), Easy/Plain English (en), Lectura Fácil (es), and 25 further locales following each language's Easy-to-Read / plain-language standard (Inclusion Europe "Information for All", Selkokieli, Lättläst, やさしい日本語, ISO 24495-1, …). Every pair is filtered by a deterministic validator suite (per-language sentence-length caps, language-ID, fidelity anchoring, number preservation, anti-parroting).
- Intended for the Live Linguist on-device live-caption simplifier. Not a general chatbot.
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4-bit