Instructions to use Helsinki-NLP/opus-mt-ja-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ja-fr 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-ja-fr")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ja-fr") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ja-fr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-ja-fr: direct link, hf CLI and curl.
- Browser
- Download file 306 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-ja-fr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-ja-fr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-ja-fr/resolve/main/pytorch_model.bin
306 MB
- Xet hash:
- 16d53886f0d0fddc593c4954bb6edf6c1729e88ef64a3af1590182af9ec2ce65
- Size of remote file:
- 306 MB
- SHA256:
- 4d9ca3bcaa498cd29e27057c3f1134978ee174354cfb662f4165e0da479ff20d
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