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update live training report
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README.md

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@@ -36,6 +36,10 @@ x = torch.randn([1, 1000]) # batch, seq_len (encoded as integer in [0, 21], 21
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out = model.log_likelihood(x)
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```
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## Reproduction status
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Live training metrics for Tranception S model using UniRef50 can be found [here](https://wandb.ai/dohlee/tranception-pytorch/reports/Tranception-training--VmlldzozODIyODI0).
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## Citation
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```bibtex
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@inproceedings{notin2022tranception,

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