Instructions to use Helsinki-NLP/opus-mt-urj-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-urj-en 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-urj-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-urj-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-urj-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-urj-en: direct link, hf CLI and curl.
- Browser
- Download file 300 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-urj-en/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-urj-en/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-urj-en/resolve/main/pytorch_model.bin
300 MB
- Xet hash:
- d92593d1941184253c27b085f326c778167badb35005bbb8a00584742fe2846c
- Size of remote file:
- 300 MB
- SHA256:
- 59e26a58cbb7eac1b5fc51a882af61a252d2ddde61c1bdafcaa1066bc8fd75a2
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