Instructions to use Helsinki-NLP/opus-mt-fr-pap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fr-pap 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-fr-pap")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-pap") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fr-pap", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-fr-pap: direct link, hf CLI and curl.
- Browser
- Download file 301 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-fr-pap/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-fr-pap/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-fr-pap/resolve/main/pytorch_model.bin
301 MB
- Xet hash:
- fd115f173d82528384ae04ef33aa65ddfbd2ecfba24fd9d1321c142c5d7b424b
- Size of remote file:
- 301 MB
- SHA256:
- f03f8873ac761219b030601e7ff1ca34442724f512a02e7d9f1a7a46363b2569
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