Translation
Transformers
PyTorch
Safetensors
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-big-zlw-zle 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-zlw-zle 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-zlw-zle")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-big-zlw-zle") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-big-zlw-zle") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7197082370177c37025c229297d94f0c0b45d5aa5b3cb17a4f0ba4121435ae68
- Size of remote file:
- 4.94 MB
- SHA256:
- 054fd9c90666b9e06ccc2174e27cd804bf0e71d2accb1e8a7022cff5c1a97dd9
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