Instructions to use Helsinki-NLP/opus-mt-sv-bem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-bem 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-bem")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-bem") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-bem") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b257ea5ee69915c9b9e9faf348113d711d8b825b5f6ef82a78b7602a72fd6de
- Size of remote file:
- 303 MB
- SHA256:
- 614c34412f0d536f81ddfc9198ed397bb33fb2263f43c1108a138b7417bd54ef
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