Instructions to use Omar-youssef/english-egyptian-arabic-translation-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Omar-youssef/english-egyptian-arabic-translation-v1 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="Omar-youssef/english-egyptian-arabic-translation-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Omar-youssef/english-egyptian-arabic-translation-v1") model = AutoModelForSeq2SeqLM.from_pretrained("Omar-youssef/english-egyptian-arabic-translation-v1") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -23,7 +23,6 @@ A fine-tuned version of [Helsinki-NLP/opus-mt-tc-big-en-ar](https://huggingface.
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This model translates English text into **Egyptian Arabic (العامية المصرية)**, the most widely spoken Arabic dialect. It was fine-tuned on Egyptian Arabic translation pairs, making it more accurate for colloquial Egyptian Arabic compared to the base model which targets Modern Standard Arabic (MSA).
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- **Developed by:** Omar Youssef
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- **Model type:** Seq2Seq Translation (MarianMT)
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- **Language(s):** English (`en`) → Egyptian Arabic (`ar`)
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- **License:** Apache 2.0
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This model translates English text into **Egyptian Arabic (العامية المصرية)**, the most widely spoken Arabic dialect. It was fine-tuned on Egyptian Arabic translation pairs, making it more accurate for colloquial Egyptian Arabic compared to the base model which targets Modern Standard Arabic (MSA).
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- **Model type:** Seq2Seq Translation (MarianMT)
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- **Language(s):** English (`en`) → Egyptian Arabic (`ar`)
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- **License:** Apache 2.0
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