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README.md
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SMaLL-100 is a compact and fast massively multilingual machine translation model covering more than 10K language pairs, that achieves competitive results with M2M-100 while being much smaller and faster. It is introduced in [this paper](https://arxiv.org/abs/2210.11621), and initially released in [this repository](https://github.com/alirezamshi/small100).
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The model architecture and config are the same as [M2M-100](https://huggingface.co/facebook/m2m100_418M/tree/main) implementation, but the tokenizer is modified to adjust language codes. So, you should load the tokenizer locally from tokenization_small100.py file for the moment.
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```
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from transformers import M2M100ForConditionalGeneration
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SMaLL-100 is a compact and fast massively multilingual machine translation model covering more than 10K language pairs, that achieves competitive results with M2M-100 while being much smaller and faster. It is introduced in [this paper](https://arxiv.org/abs/2210.11621), and initially released in [this repository](https://github.com/alirezamshi/small100).
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The model architecture and config are the same as [M2M-100](https://huggingface.co/facebook/m2m100_418M/tree/main) implementation, but the tokenizer is modified to adjust language codes. So, you should load the tokenizer locally from (tokenization_small100.py)[https://huggingface.co/alirezamsh/small100/blob/main/tokenization_small100.py] file for the moment.
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```
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from transformers import M2M100ForConditionalGeneration
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