Translation
Transformers
PyTorch
Safetensors
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-big-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-tc-big-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-tc-big-cel-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-big-cel-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-big-cel-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cef22a1d3c5f56d504c9e4256121cf9c97bd03d11bba799575cb9b4f938af91d
- Size of remote file:
- 1.14 MB
- SHA256:
- f1e21df596a8f158cc76408b270d1d39484eed7c164a0b88d055c5bf01010d2e
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