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
- Atomic Chat
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -1,7 +1,69 @@
|
|
| 1 |
---
|
| 2 |
-
|
|
|
|
| 3 |
library_name: mlx
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
- mlx
|
| 7 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
base_model: Qwen/Qwen3-0.6B
|
| 4 |
library_name: mlx
|
| 5 |
+
tags: [mlx, text-simplification, easy-language, accessibility, multilingual, qwen3]
|
| 6 |
+
language: [de, fr, en, es, ar, da, et, fi, hi, it, ja, ko, nl, pt, ru, sk, sv, tr, vi, zh, uk, ro, bg, pl, hr, nb, hu, cs]
|
|
|
|
| 7 |
---
|
| 8 |
+
|
| 9 |
+
# Qwen3-0.6B-EasyLanguage (4-bit, MLX)
|
| 10 |
+
|
| 11 |
+
LoRA fine-tune of **Qwen/Qwen3-0.6B** that rewrites live speech transcripts into easy-to-read
|
| 12 |
+
registers across **29 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
|
| 13 |
+
[Live Linguist](https://github.com/ngoldbla/live-linguist) on-device captioner.
|
| 14 |
+
Each locale follows its own national / European Easy-to-Read or plain-language standard.
|
| 15 |
+
Quantized to 4-bit for Apple-silicon inference via MLX.
|
| 16 |
+
|
| 17 |
+
It splits run-ons into short sentences, drops disfluencies, keeps names/numbers, and
|
| 18 |
+
stays in the input language. Trained on a lean prompt (no few-shots) so the register is
|
| 19 |
+
internalized — shorter prompts, lower live-caption latency.
|
| 20 |
+
|
| 21 |
+
## Evaluation (held-out test set; SARI = simplification quality)
|
| 22 |
+
| lang | SARI ft | SARI stock | chrF ft | LID ft | compliance ft |
|
| 23 |
+
| --- | --- | --- | --- | --- | --- |
|
| 24 |
+
| de | 47.56 | 32.98 | 41.93 | 1.0 | 0.985 |
|
| 25 |
+
| fr | 57.97 | 33.31 | 51.47 | 1.0 | 0.99 |
|
| 26 |
+
| es | 59.45 | 36.57 | 54.68 | 1.0 | 0.99 |
|
| 27 |
+
| en | 60.99 | 32.46 | 55.03 | 1.0 | 0.975 |
|
| 28 |
+
| ar | 50.04 | 50.11 | 46.58 | 0.99 | 0.945 |
|
| 29 |
+
| da | 53.67 | 35.58 | 51.18 | 0.99 | 0.93 |
|
| 30 |
+
| et | 47.65 | 30.48 | 50.87 | 1.0 | 0.995 |
|
| 31 |
+
| fi | 49.9 | 35.2 | 55.87 | 1.0 | 0.975 |
|
| 32 |
+
| hi | 51.87 | 35.16 | 44.18 | 0.99 | 0.805 |
|
| 33 |
+
| it | 54.0 | 49.18 | 48.83 | 1.0 | 0.8557 |
|
| 34 |
+
| ja | 8.39 | 8.29 | 41.38 | 1.0 | 0.965 |
|
| 35 |
+
| ko | 49.23 | 43.77 | 39.56 | 1.0 | 0.975 |
|
| 36 |
+
| nl | 51.68 | 38.96 | 48.21 | 0.99 | 0.89 |
|
| 37 |
+
| pt-BR | 55.34 | 37.54 | 51.92 | 1.0 | 0.755 |
|
| 38 |
+
| pt-PT | 58.17 | 38.96 | 58.38 | 1.0 | 0.93 |
|
| 39 |
+
| ru | 51.09 | 41.13 | 49.39 | 1.0 | 0.93 |
|
| 40 |
+
| sk | 51.19 | 40.59 | 46.52 | 1.0 | 0.96 |
|
| 41 |
+
| sv | 53.62 | 40.16 | 54.36 | 0.99 | 0.965 |
|
| 42 |
+
| tr | 50.51 | 31.73 | 49.61 | 0.995 | 0.97 |
|
| 43 |
+
| vi | 60.23 | 41.3 | 58.21 | 1.0 | 0.685 |
|
| 44 |
+
| zh-CN | 9.0 | 8.5 | 51.54 | 0.995 | 0.935 |
|
| 45 |
+
| uk | 52.12 | 39.63 | 51.13 | 0.995 | 0.99 |
|
| 46 |
+
| ro | 51.7 | 40.75 | 50.94 | 1.0 | 0.94 |
|
| 47 |
+
| bg | 50.83 | 34.17 | 52.76 | 0.985 | 0.98 |
|
| 48 |
+
| pl | 50.56 | 36.93 | 48.21 | 1.0 | 0.97 |
|
| 49 |
+
| hr | 51.3 | 33.88 | 50.85 | 0.995 | 0.99 |
|
| 50 |
+
| nb | 51.82 | 29.97 | 54.57 | 0.99 | 0.97 |
|
| 51 |
+
| hu | 49.74 | 38.56 | 51.06 | 1.0 | 0.985 |
|
| 52 |
+
| cs | 49.41 | 39.47 | 46.51 | 0.995 | 0.985 |
|
| 53 |
+
|
| 54 |
+
## Usage (MLX)
|
| 55 |
+
```python
|
| 56 |
+
from mlx_lm import load, generate
|
| 57 |
+
model, tok = load("ndgold/Qwen3-0.6B-EasyLanguage-4bit")
|
| 58 |
+
msgs = [{"role":"system","content":"<framework system prompt>"},
|
| 59 |
+
{"role":"user","content":"Original: <utterance>\nRewritten:"}]
|
| 60 |
+
p = tok.apply_chat_template(msgs, add_generation_prompt=True, tokenize=False, enable_thinking=False)
|
| 61 |
+
print(generate(model, tok, prompt=p, max_tokens=96))
|
| 62 |
+
```
|
| 63 |
+
|
| 64 |
+
## Sources & licenses
|
| 65 |
+
- **Base model:** Qwen3 (Apache-2.0).
|
| 66 |
+
- **German seed data:** [tum-nlp/German4All-Corpus](https://huggingface.co/datasets/tum-nlp/German4All-Corpus) (German Wikipedia, CC BY-SA).
|
| 67 |
+
- **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).
|
| 68 |
+
- Intended for the **Live Linguist** on-device live-caption simplifier. Not a general chatbot.
|
| 69 |
+
|