yfterelu/marian_eng_tig

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Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Developed by: Hadush Harya(yfterelu)

• Model type: Seq2Seq (MarianMT)
• Languages: English (en), Tigrigna (ti)
• Training data: Custom parallel dataset (tigrigna_text ↔ translated)
• Fine-tuned from: Helsinki-NLP/opus-mt-en-af (as base, if true) or scratch

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Uses

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How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

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Summary

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Environmental Impact

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language: - en - ti license: mit tags: - machine-translation - tigrigna - english datasets: - yfterelu/marian_eng_tig metrics: - sacrebleu

MarianMT English ↔ Tigrigna

This is a MarianMT model fine-tuned for English ↔ Tigrigna translation.

Details

• Developed by: Yfterelu
• Model type: Seq2Seq (MarianMT)
• Languages: English (en), Tigrigna (ti)
• Training data: Custom parallel dataset (tigrigna_text ↔ translated)
• Fine-tuned from: Helsinki-NLP/opus-mt-en-af (as base, if true) or scratch

Usage

from transformers import MarianMTModel, MarianTokenizer

model_name = "yfterelu/marian_eng_tig"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)

src_text = ["Have a good start."]
inputs = tokenizer(src_text, return_tensors="pt", padding=True, truncation=True)
outputs = model.generate(**inputs)
translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(translation)


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