Instructions to use Helsinki-NLP/opus-mt-en-sem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-sem 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-sem")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-sem") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-sem") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a2098fc564131f073284261b54b907b9ecee2482fd162ea3bd11704a3ab41c7
- Size of remote file:
- 304 MB
- SHA256:
- fe0469ad2ccf60b294803ec8d2ee915c19e7de59fc82eddb4accada7dc5e27e9
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