Translation
Transformers
PyTorch
TensorFlow
Safetensors
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-big-en-pt 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-en-pt 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-en-pt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-big-en-pt") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-big-en-pt", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87975e46a60d9c3c8ec84ef8595dbb756eb86d447fe74a8ebe4b6e7671230590
- Size of remote file:
- 1.52 MB
- SHA256:
- 3539b408a2285cd7e35a58128a29f810ad72632d3cb3de8c522cfaa5ac723be6
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