Instructions to use Helsinki-NLP/opus-mt-cel-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-cel-en 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-cel-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-cel-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-cel-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc79ebe3a80954d6c0881293604d60260293e6d09ca7b18b0b4b5433038c418c
- Size of remote file:
- 298 MB
- SHA256:
- f097b988b2f1d517912e94e87b1d0cc63e652c293cced70aa666d7921912820a
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