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--- |
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license: mit |
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--- |
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This model is provided to compare with official ESM-2 35M model. It only receives residue sequence but shares the same vocabulary with normal SaProt, |
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which means all structure(3Di) tokens are marked as ``#`` during training. |
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### Huggingface model |
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The following code shows how to load the model. |
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``` |
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from transformers import EsmTokenizer, EsmForMaskedLM |
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model_path = "/your/path/to/SaProt_35M_AF2_seqOnly" |
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tokenizer = EsmTokenizer.from_pretrained(model_path) |
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model = EsmForMaskedLM.from_pretrained(model_path) |
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#################### Example #################### |
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device = "cuda" |
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model.to(device) |
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seq = "M#E#V#Q#L#V#Q#Y#K#" |
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tokens = tokenizer.tokenize(seq) |
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print(tokens) |
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inputs = tokenizer(seq, return_tensors="pt") |
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inputs = {k: v.to(device) for k, v in inputs.items()} |
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outputs = model(**inputs) |
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print(outputs.logits.shape) |
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""" |
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['M#', 'E#', 'V#', 'Q#', 'L#', 'V#', 'Q#', 'Y#', 'K#'] |
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torch.Size([1, 11, 446]) |
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""" |
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``` |
