Instructions to use Helsinki-NLP/opus-mt-en-sk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-sk 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-en-sk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-sk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-sk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ec1815e7c26fc2ab3495d47b29dcb4cbbef1fc8350404cd7ce139c1909ca215
- Size of remote file:
- 302 MB
- SHA256:
- 1e4c2ed6e87dfd315ea440df7d302e3c5f36d7207e11b92cdee59e186fa235fc
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