Instructions to use Helsinki-NLP/opus-mt-de-ca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-de-ca 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-de-ca")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-de-ca") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-de-ca") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3d0b49bc8bc8bdb62a47a23f90229f67b70d02287953b3e88cf666f27d91196
- Size of remote file:
- 224 MB
- SHA256:
- 2789aa24da73f2f61098213a426acd8e0df8c990087e18ae814eb9e56435d018
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