SaveBertAndGpt
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README.md
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@@ -21,7 +21,7 @@ In this model, DREAM-FLUTE (consequence), we use elaborations along the "likely
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We provide a quick example of how you can try out DREAM-FLUTE (consequence) in our paper with just a few lines of code:
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```
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>>> from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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>>> model =
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>>> tokenizer = AutoTokenizer.from_pretrained("t5-3b")
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>>> input_string = "Premise: My decision-making skills are not purely based on emotions and gut. [Premise - likely consequence] I make more balanced and informed decisions. Hypothesis: My personal feelings color my judgment in this case. [Hypothesis - likely consequence] I make a decision that is not in the best interests of the company. Is there a contradiction or entailment between the premise and hypothesis?"
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We provide a quick example of how you can try out DREAM-FLUTE (consequence) in our paper with just a few lines of code:
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```
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>>> from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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>>> model = AutoModelForSeq2SeqLM.from_pretrained("allenai/System3_DREAM_FLUTE_consequence_FigLang2022")
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>>> tokenizer = AutoTokenizer.from_pretrained("t5-3b")
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>>> input_string = "Premise: My decision-making skills are not purely based on emotions and gut. [Premise - likely consequence] I make more balanced and informed decisions. Hypothesis: My personal feelings color my judgment in this case. [Hypothesis - likely consequence] I make a decision that is not in the best interests of the company. Is there a contradiction or entailment between the premise and hypothesis?"
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