Translation
Transformers
PyTorch
TensorFlow
French
Zande (individual language)
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-fr-zne with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fr-zne 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-zne")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-zne") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fr-zne") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cec8d2128c48355dffcee9d2152b5ad57397164a389232ba800e5f1a226c6659
- Size of remote file:
- 289 MB
- SHA256:
- a4a2c0dd9e561bc3a3657fa028e20a0912f7408633bef7204d1bb8cb747678d3
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