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  We evaluated the xTrimoPGLM-MLM (xTMLM) and xTrimoPGLM(100B) models on two OOD test sets, one with sequence identity lower than 0.9 with the training set (<0.9 ID) and the other with sequence identity lower than 0.5 with the training set (<0.5 ID). Each OOD dataset comprises approximately 10,000 protein sequences. The perplexity results, compared against ESM2-3B and ESM2-15B, are as follows (lower is better):
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- | Model | ESM2(3B)| ESM2 (15B) | xTMLM (1B) | xTMLM (3B) | xTMLM (10B) | xT (100B) | xT (100B)-INT4 |
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- |:--------------------|:----------:|:----------:|:----------:|:----------:|:--------------------:|:--------------------:|:--------------------:|
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- | < 0.9 ID | 7.7 | 7.3 | 9.3 | 7.8 | 7.6 | **6.7** | **6.8** |
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- | < 0.5 ID | 11.5 | 11.0 | 13.5 | 11.9 | 11.6 | **10.7** | **10.8** |
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  We evaluated the xTrimoPGLM-MLM (xTMLM) and xTrimoPGLM(100B) models on two OOD test sets, one with sequence identity lower than 0.9 with the training set (<0.9 ID) and the other with sequence identity lower than 0.5 with the training set (<0.5 ID). Each OOD dataset comprises approximately 10,000 protein sequences. The perplexity results, compared against ESM2-3B and ESM2-15B, are as follows (lower is better):
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+ | Model | ESM2(3B)| ESM2 (15B) | xTMLM (1B) | xTMLM (3B) | xTMLM (10B) | xT (100B)-INT4 |
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+ |:--------------------|:----------:|:----------:|:----------:|:----------:|:--------------------:|:--------------------:|
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+ | < 0.9 ID | 7.7 | 7.3 | 9.3 | 7.8 | 7.6 | **6.8** |
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+ | < 0.5 ID | 11.5 | 11.0 | 13.5 | 11.9 | 11.6 | **10.8** |
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