Few small nits in GPT-2's code examples
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@@ -427,7 +427,7 @@ model.to('cuda')
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with torch.no_grad():
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hidden_states_1, past = model(tokens_tensor_1)
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# past can be used to reuse precomputed hidden state in a subsequent predictions
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# (see beam-search examples in the run_gpt2.py example
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# (see beam-search examples in the run_gpt2.py example).
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hidden_states_2, past = model(tokens_tensor_2, past=past)
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```
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@@ -439,14 +439,15 @@ model = GPT2LMHeadModel.from_pretrained('gpt2')
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model.eval()
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# If you have a GPU, put everything on cuda
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tokens_tensor_1 = tokens_tensor.to('cuda')
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tokens_tensor_1 = tokens_tensor_1.to('cuda')
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tokens_tensor_2 = tokens_tensor_2.to('cuda')
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model.to('cuda')
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# Predict all tokens
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with torch.no_grad():
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predictions_1, past = model(tokens_tensor_1)
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# past can be used to reuse precomputed hidden state in a subsequent predictions
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# (see beam-search examples in the run_gpt2.py example
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# (see beam-search examples in the run_gpt2.py example).
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predictions_2, past = model(tokens_tensor_2, past=past)
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# get the predicted last token
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