Instructions to use Helsinki-NLP/opus-mt-sv-tw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-tw 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-tw")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-tw") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-tw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c338de8dbf67bdf9a0830ef39521bbc514a40fec5f48af50bf2a71b7c52e084
- Size of remote file:
- 301 MB
- SHA256:
- 09587622f36e45d0c75d4a92a7999138f28162696e8934105c4d4d0d5a189715
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