Translation
Transformers
PyTorch
TensorFlow
Safetensors
Arabic
English
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-big-en-ar 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-ar 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-ar")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-big-en-ar") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-big-en-ar") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a23a100ea2ea732990d497e65965f38ddf000bce18c1686d091fe347e18cccf9
- Size of remote file:
- 2.11 MB
- SHA256:
- 1285375ccee419aa268dec1b666e164c869e7c59dfe264e0bab4d684777c0dae
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