Translation
Transformers
Safetensors
English
Azerbaijani
m2m_100
text2text-generation
azerbaijani
nllb
english-azerbaijani
Instructions to use LocalDoc/nllb-3.3b-en-az with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalDoc/nllb-3.3b-en-az with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="LocalDoc/nllb-3.3b-en-az")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LocalDoc/nllb-3.3b-en-az") model = AutoModelForSeq2SeqLM.from_pretrained("LocalDoc/nllb-3.3b-en-az", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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| Qwen3.6-35B-A3B | 60.39 | 33.57 | 91.23 |
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| NLLB-200-3.3B (base, zero-shot) | 59.03 | 31.76 | 89.86 |
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Fine-tuning improved the base NLLB-3.3B by **+10.97 chrF++** (59.03 →
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## Example Translations
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| Qwen3.6-35B-A3B | 60.39 | 33.57 | 91.23 |
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| NLLB-200-3.3B (base, zero-shot) | 59.03 | 31.76 | 89.86 |
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Fine-tuning improved the base NLLB-3.3B by **+10.97 chrF++** (59.03 → 70.00) and **+2.89 COMET-DA** (89.86 → 92.75). The result surpasses Google Translate, DeepSeek-V4-Pro, GPT-4.1, Gemma-3-31B, and Qwen-35B, and comes within 0.8 chrF++ of GPT-5.4-mini and Gemini-2.5-flash.
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## Example Translations
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