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README.md
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---
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license: mit
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language:
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- en
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- ar
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- ca
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- de
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- et
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- fa
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- id
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- ja
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- lv
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- mn
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- sl
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- sv
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- ta
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- tr
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- zh
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metrics:
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- bleu
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pipeline_tag: translation
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datasets:
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- facebook/covost2
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---
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# Model Name
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This is a multilingually fine-tuned version of [NLLB](https://arxiv.org/abs/2207.04672) based on [nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) using the text data of CoVoST2 (En -> 15).
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("johntsi/nllb-200-distilled-600M_covost2_en-to-15")
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model = AutoModelForSeq2SeqLM.from_pretrained("johntsi/nllb-200-distilled-600M_covost2_en-to-15")
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model.eval()
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model.to("cuda")
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text = "Translate this text to German."
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inputs = tokenizer(text, return_tensors="pt").to("cuda")
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outputs = model.generate(
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**inputs,
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num_beams=5,
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forced_bos_token_id=tokenizer.lang_code_to_id["deu_Latn"]
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)
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translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(translated_text)
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```
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## Results: BLEU scores on CoVoST2 test (text part)
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| Model | Ar | Ca | Cy | De | Et | Fa | Id | Ja | Lv | Mn | Sl | Sv | Ta | Tr | Zh | Average |
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|:------------------------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:-------:|
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| nllb-200-distilled-600M (original) | 20.0 | 39.0 | 26.3 | 35.5 | 23.4 | 15.7 | 39.6 | 21.8 | 14.8 | 10.4 | 30.3 | 41.1 | 20.2 | 21.1 | 34.8 | 26.3 |
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| nllb-200-distilled-600M_covost2_en-to-15 | 28.5 | 46.3 | 35.5 | 37.1 | 31.5 | 29.2 | 45.2 | 38.4 | 29.1 | 22.0 | 37.7 | 45.4 | 29.9 | 23.0 | 46.7 | 35.0 |
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| nllb-200-distilled-1.3B (original) | 23.3 | 43.5 | 33.5 | 37.9 | 27.9 | 16.6 | 41.9 | 23.0 | 20.0 | 13.1 | 35.1 | 43.8 | 21.7 | 23.8 | 37.5 | 29.5 |
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| nllb-200-distilled-1.3B_covost2_en-to-15 | 29.9 | 47.8 | 35.6 | 38.8 | 32.7 | 29.9 | 46.4 | 39.5 | 29.9 | 21.7 | 39.3 | 46.8 | 31.0 | 24.4 | 48.2 | 36.1 |
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