Instructions to use Helsinki-NLP/opus-mt-en-ine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ine 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-ine")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ine") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ine") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7203308f1e145c53be0d2eadeeeaed31299b460b2d994a5188445c09f6d7285c
- Size of remote file:
- 304 MB
- SHA256:
- 7590ce8604f15df34c5923952a75630aeeef3c61d0389162e6cf8e67fc9e7090
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