Instructions to use Helsinki-NLP/opus-mt-nl-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-nl-en 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-nl-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-nl-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-nl-en") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a8fc071d3f25b5c64ec7a99cbc769df9f20f7f6d903f3b05963b5b45a0c5cf5
- Size of remote file:
- 316 MB
- SHA256:
- 70243188530be305eaee44a120fc768a1f7f52abad2f7bb4f87b70bd4fe2a6c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.