Instructions to use Helsinki-NLP/opus-mt-guw-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-guw-sv 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-guw-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-guw-sv") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-guw-sv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-guw-sv: direct link, hf CLI and curl.
- Browser
- Download file 289 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-guw-sv/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-guw-sv/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-guw-sv/resolve/main/pytorch_model.bin
289 MB
- Xet hash:
- e94ecb47d55c61e882ab65af223f17232438ad80ba244fe6d9a890a771f3ab3a
- Size of remote file:
- 289 MB
- SHA256:
- a89f52cd830e3d13c10cdb76d3289cedfc9abe1f93b82dd40fcc3ba8deb9c901
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