| --- |
| library_name: transformers |
| tags: [] |
| --- |
| |
| See UDEV on starting a Docker with necessary requirements |
|
|
| ``` |
| import torch |
| from udev.models.amplify.modeling_amplify import AMPLIFY |
| |
| device = torch.device("cuda") # only cuda is supported |
| model = AMPLIFY.from_pretrained('GleghornLab/AMPLIFY_350M', token=token).to(device) |
| tokenizer = EsmTokenizer.from_pretrained('GleghornLab/AMPLIFY_350M', token=token) |
| |
| sequences = ['SEQWENCE', 'MEAEGAVE'] # list of seqs: str |
| tokens = tokenizer(sequences, return_tensors='pt', padding=True, pad_to_multiple_of=8) |
| tokens = {k: v.to(device) for k, v in tokens.items()} |
| |
| out = model( |
| src=tokens['input_ids'], |
| pad_mask=tokens['attention_mask'].float(), |
| output_hidden_states=True, |
| output_attentions=True |
| ) |
| ``` |
