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cutiesRun28-05-2020-roberta-base-evidenceAlignment
yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment
cutiesRun28-05-2020-roberta-base-evidenceAlignment is a text classification model from yevhenkost. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
Pretrained model for evidence alignment on cutietestrun28May2020 dataset. The task was binary prediction whether the claim and evidence are relevant to each other. The model was built as a part of CEASystem.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Mar 13, 2024
- Updated
- Mar 13, 2024
- SHA
- 919fb4d0
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Model card
From the Hugging Face model README
Pretrained model for evidence alignment on cutietestrun28May2020 dataset. The task was binary prediction whether the claim and evidence are relevant to each other. The model was built as a part of CEASystem.
Usage
model = transformers.AutoModelForSequenceClassification.from_pretrained("yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment")
tokenizer = transformers.AutoTokenizer.from_pretrained("yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment")
claim_evidence_pairs = [
["The water is wet", "The sky is blue"],
["The car crashed", "Driver could not see the road"]
]
tokenized_inputs = tokenizer.batch_encode_plus(
predict_pairs,
return_tensors="pt",
padding=True,
truncation=True
)
preds = model(**tokenized_batch_input)
# logits: preds.logits
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Languages
- en
- Created
- Mar 13, 2024
- Updated
- Mar 13, 2024