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20 lines
605 B
Python
20 lines
605 B
Python
import torch
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from modules import shared
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def get_next_logits(prompt):
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tokens = shared.tokenizer.encode(prompt, return_tensors='pt').cuda()
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output = shared.model(input_ids=tokens)
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scores = output['logits'][-1][-1]
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probs = torch.softmax(scores, dim=-1, dtype=torch.float)
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topk_values, topk_indices = torch.topk(probs, k=20, largest=True, sorted=True)
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topk_values = [f"{float(i):.5f}" % i for i in topk_values]
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output = ''
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for row in list(zip(topk_values, shared.tokenizer.convert_ids_to_tokens(topk_indices))):
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output += f"{row[0]} {row[1]}\n"
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return output
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