Instructions to use Helsinki-NLP/opus-mt-fr-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fr-mt 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-mt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-mt") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fr-mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 836866998f7f70463e728923c41ad17a3a03f378dcc7f2b81ecf220fb3574529
- Size of remote file:
- 296 MB
- SHA256:
- fad0f54025737a51cad042328cdc017fc27be10d0f07e02d614b8537f7e6dec7
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