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The model detect claim-worthiness of a given text. This model is a part of an automatic fact-checking pipeline.

The model is trained on data for Task 1 from CLEF2021-CheckThat and CLEF2024-CheckThat

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

  • Developed by: [More Information Needed]
  • Model type: transformer
  • Language(s) (NLP): [More Information Needed]
  • License: [More Information Needed]
  • Finetuned from model [optional]: FacebookAI/xlm-roberta-base

Uses

The model is fine-tuned on a multilingual dataset, combining english, spanish, arabic, bulgarian, turkish, and dutch. It is meant to be used as zero-shot model for multilingual text data.

tokenizer = XLMRobertaTokenizer.from_pretrained("FacebookAI/xlm-roberta-base")
model = XLMRobertaForSequenceClassification.from_pretrained("SophieTr/xlm-roberta-base-claim-detection-clef21-24")

inputs = tokenizer(
    sentence_array, 
    return_tensors="pt", 
    padding=True, 
    truncation=True
)

with torch.no_grad():
    logits = model(**inputs).logits
    
predictions = [logits[i].argmax().item() for i,t in enumerate(logits)]
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Safetensors
Model size
278M params
Tensor type
F32
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