Mhassanen
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nllb-200-600M-En-Ar

Text2Text Generation

Transformers

Safetensors

m2m_100

Inference Endpoints

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Mhassanen commited on May 26

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 # Model Card for Model ID
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-## Model Details
-### Model Description
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
 # Model Card for Model ID
+## nllb-200-600M-En-Ar-finetuned
+This model is a fine-tuned version of the NLLB-200-600M model, specifically adapted for translating from English to Egyptian Arabic. Fine-tuned on a custom dataset of 12,000 samples, it aims to provide high-quality translations that capture the nuances and colloquial expressions of Egyptian Arabic.
+The dataset used for fine-tuning was collected from high-quality transcriptions of videos, ensuring the language data is rich and contextually accurate.
+### Model Details
+- **Base Model**: [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M)
+- **Language Pair**: English to Egyptian Arabic
+- **Dataset**: 12,000 custom translation pairs
+### Usage
+To use this model for translation, you can load it with the `transformers` library:
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+model_name = "Mhassanen/nllb-200-600M-En-Ar-finetuned"
+tokenizer = AutoTokenizer.from_pretrained(model_name, src_lang="eng_Latn", tgt_lang="arz_Arab")
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+def translate(text):
+    inputs = tokenizer(text, return_tensors="pt", padding=True)
+    translated_tokens = model.generate(**inputs)
+    translated_text = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)
+    return translated_text
+text = "Hello, how are you?"
+print(translate(text))
+```
+### Performance
+The model has been evaluated on a validation set to ensure translation quality. While it excels at capturing colloquial Egyptian Arabic, ongoing improvements and additional data can further enhance its performance.
+### Limitations
+- **Dataset Size**: The custom dataset consists of 12,000 samples, which may limit coverage of diverse expressions and rare terms.
+- **Colloquial Variations**: Egyptian Arabic has many dialectal variations, which might not all be covered equally.
+### Acknowledgements
+This model builds upon the [NLLB-200-600M](https://huggingface.co/facebook/nllb-200-600M) developed by Facebook AI, fine-tuned to cater specifically to the Egyptian Arabic dialect.
+Feel free to contribute or provide feedback to help improve this model!