Model Description
arXivBERT is a series of models trained on a time-based unit. If you are looking for the best performance on scientific corpora, please use the model from 2020 directly.
Why ?arXivBERT
- Specialized in Scientific Content: Trained on a large dataset of arXiv papers, ensuring high familiarity with scientific terminology and concepts.
- Versatile in Applications: Suitable for a range of NLP tasks, including but not limited to text classification, keyword extraction, summarization of scientific papers, and citation prediction.
- Evolutionary Insights: Continuous pre-training captures the long-term relationships and changes within the corpus.
How to Use?
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("folderPath/year")
model = AutoModel.from_pretrained("folderPath/wholewordtokenizer")
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