Instructions to use Helsinki-NLP/opus-mt-sv-ht with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-ht 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-ht")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-ht") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-ht", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-sv-ht: direct link, hf CLI and curl.
- Browser
- Download file 276 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-sv-ht/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-sv-ht/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-sv-ht/resolve/main/pytorch_model.bin
276 MB
- Xet hash:
- 022fba56330d9d156d1f6948f17e188747d33a99cd19c25a6d93715bb246b64f
- Size of remote file:
- 276 MB
- SHA256:
- 7c132555d98e9a4e5581137ad58ad77116a55f1ea10c773e8d8a82896c9f4fc9
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