In this article, we will explore how we can use Llama2 for Topic Modeling without the need to pass every single document to the model. Instead, we will leverage BERTopic, a modular topic modeling technique that can use any LLM for fine-tuning topic representations.
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome - GitHub - jerryji1993/DNABERT: DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
A few years ago, creating a chatbot -as limited as they were back then- could take months ��, from designing the rules to actually writing thousands of answers to cover some of the conversation…
T. Gao, X. Yao, and D. Chen. (2021)cite arxiv:2104.08821Comment: Accepted to EMNLP 2021. The code and pre-trained models are available at https://github.com/princeton-nlp/simcse.
T. Gao, X. Yao, and D. Chen. (2021)cite arxiv:2104.08821Comment: Accepted to EMNLP 2021. The code and pre-trained models are available at https://github.com/princeton-nlp/simcse.
A. Mahapatra, S. Nangi, A. Garimella, and A. N. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, page 942--951. Abu Dhabi, United Arab Emirates, Association for Computational Linguistics, (December 2022)
S. Toshniwal, P. Xia, S. Wiseman, K. Livescu, and K. Gimpel. Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference, page 111--120. Punta Cana, Dominican Republic, Association for Computational Linguistics, (November 2021)