Instructions to use Helsinki-NLP/opus-mt-en-uk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-uk 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="Helsinki-NLP/opus-mt-en-uk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-uk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-uk", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1da4c05f690f73ec7c1fd0b88624334e69e6504910dde3f017e599002c0a7efe
- Size of remote file:
- 305 MB
- SHA256:
- 1fc8dc07ff5880253c0a51946f28ee4977efb84fa4e4586258994845b7384780
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.