Instructions to use Helsinki-NLP/opus-mt-en-tvl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-tvl 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-tvl")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-tvl") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-tvl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e68e5112e424f794bb0331a1618048534fb445c6c8671339f54e70445c835ae6
- Size of remote file:
- 257 MB
- SHA256:
- cf48fd7391b366b046f31cae6e5e1e7d55b545e37e923abe89d55acff244c3f1
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