Instructions to use Helsinki-NLP/opus-mt-war-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-war-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-war-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-war-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-war-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-war-en: direct link, hf CLI and curl.
- Browser
- Download file 194 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-war-en/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-war-en/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-war-en/resolve/main/pytorch_model.bin
194 MB
- Xet hash:
- a27aa9958481d47e9cb0a637f2a8a67065567d9b9d2ac5801f921e8df4b97a67
- Size of remote file:
- 194 MB
- SHA256:
- 185f8aa8c63ab409ba6dbf44c16b58b29891d59b9dc1753416a83050478aaafd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.