Instructions to use pjait/disbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pjait/disbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pjait/disbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pjait/disbert-base") model = AutoModelForSequenceClassification.from_pretrained("pjait/disbert-base") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
Model Details
- Developed by: Arkadiusz Modzelewski
- Model type: BERT (bert-base-uncased) fine-tuned for binary text classification to detect disinformation
- Language(s) (NLP): English
- Finetuned from model: google-bert/bert-base-uncased fine-tuned
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