Instructions to use Helsinki-NLP/opus-mt-en-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ru 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-ru")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ru") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ru", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-en-ru: direct link, hf CLI and curl.
- Browser
- Download file 307 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-en-ru/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-en-ru/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-en-ru/resolve/main/pytorch_model.bin
307 MB
- Xet hash:
- f3d2e0a9862200b80288dffb3842d71b92399367a30cc73ec13e1b3636f11e65
- Size of remote file:
- 307 MB
- SHA256:
- d15fa58c6bc3efd3629c1b6b86d9aa6d15d2751a4620aa4cdd7eed7b5cbe583b
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