Instructions to use Helsinki-NLP/opus-mt-bem-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-bem-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-bem-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-bem-sv") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-bem-sv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fcaaa267bfc7f99e33db5f866bfb98f896264812e630547545d024a68bcb623c
- Size of remote file:
- 303 MB
- SHA256:
- dbe331d3e229d1d760595d664d39ab84bfd331ac49761700ed5e8d0078ca1843
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