Instructions to use Helsinki-NLP/opus-mt-en-gem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-gem 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-gem")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-gem") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-gem") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaafc4ed3caf2a869bc398440b55f94f3f6a5f8a119cc0c385e5caded1fc076e
- Size of remote file:
- 295 MB
- SHA256:
- 37747559ebfc93a8138e4c6c8b9583b5ec135d200e1b887bb2f2861861ca0196
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