Instructions to use Helsinki-NLP/opus-mt-fr-tw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fr-tw 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-tw")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-tw") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fr-tw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0a1197d4e5c4eaa8dcdd53ab1c00515980faaeec6ceaa48a5297ff1d7b1a55d
- Size of remote file:
- 302 MB
- SHA256:
- 936f6f3d9165fe770db93d933ceaef1ca457237621d65c5b5ffb4b874b5554d2
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