Instructions to use Helsinki-NLP/opus-mt-sv-sg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-sg 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-sv-sg")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-sg") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-sg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-sv-sg: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-sv-sg/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-sv-sg/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-sv-sg/resolve/main/pytorch_model.bin
272 MB
- Xet hash:
- 042922129e845357019af0a85e772867a75c864bd6acf47dbb739649e8e119f0
- Size of remote file:
- 272 MB
- SHA256:
- 727eee5bd2eb959676053f43d1d1d53b8318f020125e575dd21f40fefbfff074
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