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:
- 12ee4da77554bf2e5251611e154a8791043ee6fed80e96d702dbe632419f188e
- Size of remote file:
- 604 MB
- SHA256:
- ac090df098d2b66694744ff7d4e1b24288a603aa340730d9b454687053661488
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