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I understand this is for ESM3, but I am encountering an issue with embedding in ESM2. I have two GPUs, and while performing embedding, I consistently run out of memory...
Thanks for providing this comprehensive model open-source. I was wondering what the correct sequence of predictions is: In your examples, e.g. with the Carbonic Anhydrase (2vvb) the following order is...
Hi, I am processing lots of sequences in a fasta file but esm3-small model failed on the sequence "EHVAATHKTGLDALAELTGAALNSVEKLSELQFQTVRASLEDSTEQGKRVFDARSLHELTALQSEVSQPTEKLVAYGRHLYQIAAGTHAEWRKVAQTRA". I tried reducing the sequence to see where exactly it failed...
How can i input 2 chains into ESM3 to predict structure? I tried ":" in the sequence like esm2, but returned an error
Not found Residue Annotations vocabulary file data/uniref90_and_mgnify90_residue_annotations_gt_1k_proteins.csv in repo.
Would it be possible to implement a function to generate all-atom PDB outputs including sidechains?
my code like this: > model = ESM3.from_pretrained(model_name = "./huggingface/hub/models--EvolutionaryScale--esm3-sm-open-v1/snapshots/66ecd636588d3100e13598a5720678db6583d01c/", device=torch.device("cpu")) and give the error: `--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [27], [line 1](vscode-notebook-cell:?execution_count=27&line=1) ----> [1](vscode-notebook-cell:?execution_count=27&line=1) model...
How can we get attention weights from example sequence and structure? There were no arguments to get attention weights in transformer blocks, unlike esm2.
Hi, when using esm3 model to generate embeddings, I face a new error: ``` File "/gpfs/radev/scratch/ying_rex/tl688/esm3/esm/test_esm3.py", line 1, in from esm.models.esm3 import ESM3 File "/gpfs/radev/scratch/ying_rex/tl688/esm3/esm/esm/models/esm3.py", line 13, in from esm.layers.regression_head...
Hi, thank you for the great job! There is a return which contains attention_contacts in esm2, and the code is: results = model(batch_tokens, repr_layers=[33], return_contacts=True). However, i cannot find similar...