Instructions to use Helsinki-NLP/opus-mt-sv-pag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-pag 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-pag")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-pag") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-pag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b24fcc4a0d6ec4aa0356f5c3e134a3de40db2e76abf7813bb6013ae2dee51a3
- Size of remote file:
- 301 MB
- SHA256:
- e69c7ab547601bf7ab51940d61e8557e54e974dc2e9f744b9fb28e9bf1a0b7e9
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