Natural Language Processing(NLP) Based On Generative AI Using Transformers
| dc.contributor.advisor | Tóth, Erzsébet | |
| dc.contributor.author | Khan, Dawood Ahmad | |
| dc.contributor.department | DE--Informatikai Kar | |
| dc.date.accessioned | 2024-06-23T18:33:49Z | |
| dc.date.available | 2024-06-23T18:33:49Z | |
| dc.date.created | 2024-04-13 | |
| dc.description.abstract | This thesis delves into the forefront of Natural Language Processing (NLP) by leveraging cutting-edge Transformer models. Through the utilization of technologies like PyPDF2, python-dotenv, faiss-cpu, Streamlit, and Langchain, a robust NLP framework is constructed. Langchain serves as the cornerstone, enhancing both language generation and comprehension. PyPDF2 facilitates seamless integration with PDF documents, while python-dotenv ensures secure management of environment variables. By combining state-of-the-art libraries with transformative AI models, this study showcases the profound impact on document processing, virtual assistants, and beyond, pushing the boundaries of NLP towards more natural and dynamic interactions. | |
| dc.description.course | Programtervező informatikus | |
| dc.description.degree | BSc/BA | |
| dc.format.extent | 47 | |
| dc.identifier.uri | https://hdl.handle.net/2437/374611 | |
| dc.language.iso | en | |
| dc.rights.access | Hozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében. | |
| dc.subject | Natural Language Processing | |
| dc.subject | PDF ChatBot | |
| dc.subject | Natural Language Generation | |
| dc.subject | Natural Language Understanding | |
| dc.subject | Python | |
| dc.subject | Generative AI | |
| dc.subject.dspace | Informatics | |
| dc.title | Natural Language Processing(NLP) Based On Generative AI Using Transformers |
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