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Description
Description:
To help users understand different machine translation techniques, add a notebook that applies multiple models on the same dataset and compares results.
Tasks:
- Compare Statistical Machine Translation (SMT), Seq2Seq, Transformer models (Google's T5, OpenAI's GPT, Meta’s M2M-100).
- Provide BLEU scores and human evaluation insights.
- Summarize key advantages and limitations of each approach.
- Name the notebook machine_translation_comparison.ipynb.
- Update the README file with relevant references.