Translation
Transformers
Safetensors
m2m_100
text2text-generation
language
linguistics
low-resource
tatoeba
nllb
machine-translation
gronings
Instructions to use Tom9358/nllb-tatoeba-gos-nld-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tom9358/nllb-tatoeba-gos-nld-v1 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="Tom9358/nllb-tatoeba-gos-nld-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tom9358/nllb-tatoeba-gos-nld-v1") model = AutoModelForSeq2SeqLM.from_pretrained("Tom9358/nllb-tatoeba-gos-nld-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b199f657908abf60be2ea13410dfa59761a6f94d869f3897cd1424724c213754
- Size of remote file:
- 5 GB
- SHA256:
- 27d735fb19877dd3e252b5c7a53538bc0dd262b2ecc0b3d2af33883fea300921
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