Translation
Transformers
ONNX
Safetensors
Japanese
English
marian
text2text-generation
LiteRT
Helsinki-NLP/tatoeba
openlanguagedata/flores_plus
teradata
Instructions to use Teradata/opus-mt-ja-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Teradata/opus-mt-ja-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="Teradata/opus-mt-ja-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Teradata/opus-mt-ja-en") model = AutoModelForSeq2SeqLM.from_pretrained("Teradata/opus-mt-ja-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Teradata/opus-mt-ja-en: direct link, hf CLI and curl.
- Browser
- Download file 3.95 MB
-
https://huggingface.co/Teradata/opus-mt-ja-en/resolve/main/tokenizer.json
- Command line
-
hf download hf://Teradata/opus-mt-ja-en/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Teradata/opus-mt-ja-en/resolve/main/tokenizer.json
3.95 MB
File too large to display, you can check the raw version instead.