Commit
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6334b7a
1
Parent(s):
1b7fa3a
Add model usage code
Browse files
README.md
CHANGED
@@ -14,7 +14,7 @@ The model classifies an *appraisal* given a sentence and is trained on [ALOE](ht
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**Output:** logits (in order of labels)
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**Model architecture**:
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**Developed by:** Jiamin Yang
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@@ -48,8 +48,12 @@ from openprompt.plms import load_plm
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from openprompt.prompts import ManualTemplate
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from openprompt.prompts import ManualVerbalizer
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from openprompt import PromptForClassification
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plm, tokenizer, model_config, WrapperClass = load_plm('roberta', 'roberta-large')
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template_text = 'The sentence {"placeholder":"text_a"} has the label {"mask"}.'
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@@ -67,5 +71,34 @@ state_dict = checkpoint['model_state_dict']
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del state_dict['prompt_model.plm.roberta.embeddings.position_ids']
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prompt_model.load_state_dict(state_dict)
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```
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**Output:** logits (in order of labels)
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**Model architecture**: OpenPrompt_+RoBERTa
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**Developed by:** Jiamin Yang
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from openprompt.prompts import ManualTemplate
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from openprompt.prompts import ManualVerbalizer
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from openprompt import PromptForClassification
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from openprompt.data_utils import InputExample
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from openprompt import PromptDataLoader
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torch.cuda.set_device(1)
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checkpoint_file = 'upload_version/empathy-appraisal-span.pt'
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plm, tokenizer, model_config, WrapperClass = load_plm('roberta', 'roberta-large')
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template_text = 'The sentence {"placeholder":"text_a"} has the label {"mask"}.'
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del state_dict['prompt_model.plm.roberta.embeddings.position_ids']
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prompt_model.load_state_dict(state_dict)
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# use the model
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dataset = [
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InputExample(
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guid = 0,
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text_a = "I am sorry for your loss",
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),
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InputExample(
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guid = 1,
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text_a = "It's not your fault",
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),
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]
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data_loader = PromptDataLoader(dataset=dataset,
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template=template,
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tokenizer=tokenizer,
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tokenizer_wrapper_class=WrapperClass,
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max_seq_length=512,
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batch_size=2,
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shuffle=False,
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teacher_forcing=False,
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predict_eos_token=False,
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truncate_method='head')
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prompt_model.eval()
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with torch.no_grad():
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for batch in data_loader:
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logits = prompt_model(batch.to('cuda'))
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preds = torch.argmax(logits, dim = -1)
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print(preds) #[8, 5]
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```
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