Instructions to use Helsinki-NLP/opus-mt-sv-chk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-chk 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-chk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-chk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-chk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bafd1666e5535f903fe1573582f7f2c2765354717ed7e8c9386ef4e6a2449d3
- Size of remote file:
- 300 MB
- SHA256:
- 0c751fcd2927f6581f10d7423bf3064efd38281c8936b282557d34d1a34bd5d4
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