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fix: Corrected code instructions in README.md #142

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fix: Corrected code instructions in README.md #142

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -126,7 +126,7 @@ class MyModel(torch.nn.Module):
# - If it's an attention mask then if will be torch.LongTensor of shape [batch_size, sequence_length, sequence_length].
# In this case, it's a mask indicating which tokens in the sequence should be attended by other tokens in the sequence.
# `output_all_encoded_layers`: whether to output results of all encoder layers, default, True
encoding = deberta.bert(input_ids)[-1]
encoding = self.deberta(input_ids)[-1]

# 2. Change your tokenizer with the tokenizer built-in DeBERta
from DeBERTa import deberta
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