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@@ -18,7 +18,7 @@ The dataset is ~500k sequences in total, and the model was trained on about 5% o
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  The tokenizer uses bos, eos, and pad special tokens where each sequence is padded to length 512.
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- The purpose of this model was simply to build my own version of NVIDIA's ProtGPT.
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  Upon completion of training, the model will be properly evaluated, looking at perplexity, energy of proteins generated, and AlphaFold 3 pLDDT/pTM scores
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  The tokenizer uses bos, eos, and pad special tokens where each sequence is padded to length 512.
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+ The purpose of this model was simply to build my own version of NVIDIA's ProtGPT. After this model is completed, I will be looking to add control tags to generate sequences based on a given function for a specific organism.
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  Upon completion of training, the model will be properly evaluated, looking at perplexity, energy of proteins generated, and AlphaFold 3 pLDDT/pTM scores
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