Instructions to use Helsinki-NLP/opus-mt-en-trk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-trk 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-trk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-trk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-trk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee7f47f9d691a9e01cab24e11238f48e01345cd1a8ae1a139933a4e83b8b80b9
- Size of remote file:
- 305 MB
- SHA256:
- 8382c39effafc5e3b9f5b0fcdcd10a7efbc551ef57398b6bf175d2e986ecec86
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