Instructions to use Helsinki-NLP/opus-mt-en-ROMANCE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ROMANCE 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-ROMANCE")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ROMANCE") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ROMANCE") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65552c45c5df5fb9693e5379694eb617cef807ba78e24b89666c93e099efd76e
- Size of remote file:
- 310 MB
- SHA256:
- 5f7fd32fabec57c352fcb100c553d5e2b543426563497821826faa3546c70ae3
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