Instructions to use Helsinki-NLP/opus-mt-chk-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-chk-es 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-chk-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-chk-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-chk-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aae45c3814d1ba924bc61b1db54ce83166ddc02350c68eccc6d23c531202bcc0
- Size of remote file:
- 302 MB
- SHA256:
- 68a7987b27f6af7e4ae468e09087af6fab495fa0847a21d5dc55c0b1dec0ee9e
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