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@@ -116,4 +116,18 @@ prompt = "mnli hypothesis: Your contributions were of no help with our students'
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  "premise: Your contribution helped make it possible for us to provide our students with a quality education. target:"
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  out = generator(prompt, return_full_text=False, max_new_tokens=5, top_k=1)
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  # [{'generated_text': ' contradiction'}]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  "premise: Your contribution helped make it possible for us to provide our students with a quality education. target:"
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  out = generator(prompt, return_full_text=False, max_new_tokens=5, top_k=1)
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  # [{'generated_text': ' contradiction'}]
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+ ```
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+
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+ You can create prompt-like inputs for the model using the `data_utils.py` script provided.
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+ ```python
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+ from datasets import load_dataset
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+ from data_utils import form_text, split_text
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+
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+ dataset = load_dataset('glue', 'mnli', split='validation_mismatched')
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+ dataset = dataset.map(
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+ form_text, remove_columns=['hypothesis', 'premise','label', 'idx'])
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+ # dataset[0] {'text': "mnli hypothesis: Your contributions were of no help with our students' education. premise: Your contribution helped make it possible for us to provide our students with a quality education. target: contradiction<|endoftext|>"}
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+ dataset = dataset.map(split_text, remove_columns=['text'])
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+ # dataset[0] {'prompt_text': "mnli hypothesis: Your contributions were of no help with our students' education. premise: Your contribution helped make it possible for us to provide our students with a quality education. target:",
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+ # 'class_label': 'contradiction'}
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  ```