The project's goal is to use different Deep Learning techniques - T5 Transformer, Encoder & Decoder with BiLSTM models, and NLP to generate coherent summaries – to generate brief descriptions of news stories.
- Updated
- Jupyter Notebook
#
t5-base
Here are 31 public repositories matching this topic...
Repository containing the project for the course on Business and Project Management at the University of Pisa (A.Y. 2022/2023) realized by Fabiano Pilia, Emanuele Tinghi and Matteo Dal Zotto.
python natural-language-processing sentiment-analysis tensorflow transformer bart summarization text-processing pegasus kaggle-dataset amazon-reviews huggingface-transformers generative-ai t5-base t5-large text-to-text-generation
- Updated
- Jupyter Notebook
Derived from Medical Literature Development: Injecting domain expertise into T5 via precision vocabulary-guided masking. 源自医学文献开发：通过精准词库引导遮蔽，为 T5 注入领域专业知识。医学文献開発に基づく実装：高精度な語彙ガイド付きマスキングにより、T5モデルにドメイン専門知識を注入。(機械翻訳)
nlp transformers preprocessing mt5 fine-tuning pre-training t5 google-research t5-model t5-base t5-small
- Updated
- Python
Finetuned FLAN-T5 to translate English to Hawaiian Pidgin
nlp language translation pidgin transformers hawaii english transformer t5 t5-model pidgin-bible llm t5-base flan-t5
- Updated
- Jupyter Notebook
A news headline generator finetuned on T5-base.
nlp natural-language-processing transformers semantic-similarity rouge-l fine-tuning news-headline-generation pytorch-lightning t5-model t5-base
- Updated
- Jupyter Notebook
This project summarizes large text from any article to a smaller version without any loss in context. It uses the T5 Base transformer model.
- Updated
- Jupyter Notebook
This repository hosts an AI-powered chatbot using LLaMA 2 to promote constitutional literacy. It provides interactive answers on citizen rights, fundamental duties, and legal provisions. Built with Hugging Face Transformers, Streamlit, and a user-friendly UI, it simplifies legal knowledge for all. Contributions and improvements are welcome! 🚀
- Updated
- Jupyter Notebook
This project provides code for fine-tuning T5/mT5 models on data preprocessed by T5-Refiner-DomainFocus, enabling improved performance on domain-specific text. 本项目提供针对经过 T5-Refiner-DomainFocus 预处理后的数据进行微调训练的代码，便于在专业领域文本上优化 T5/mT5 模型性能。本プロジェクトは、T5-Refiner-DomainFocus によって前処理されたデータを用いた T5/mT5 モデルのファインチューニング用コードを提供し、専門分野のテキストにおける性能向上を可能にします。（機械翻訳）
- Updated
- Python
Fine-tuning the T5-base model using parts of the CNN/DailyMail dataset using PyTorch Lightning.
- Updated
- Jupyter Notebook
Fine-Tuning LLM for summarization in Portuguese (T5)
- Updated
- Jupyter Notebook
A resume matching tool. Finds the top 5 best matching resumes for each job description provided.
- Updated
- Jupyter Notebook
A django application that allows you to summarize the content of a press article found by a user. It uses the T5 model for summarization, the LDA algorithm for topic modeling and Selenium to scrape the content of the linked article.
- Updated
- Python
German-to-English fine-tuned T5 base model with dependency-parsing enhancement.
- Updated
- Python
A NLP based summarizer which can summarize news article.
- Updated
- Jupyter Notebook
A Parameter Efficient Histopathology Visual Question Answering System based on T5-Base
- Updated
- Python
This repository consists of the implementation of the paper "Automatic Ellipsis Reconstruction in Coordinated German Sentences based on Text-To-Text Transfer Transformers" which is accepted at 27th International Conference on Text, Speech and Dialogue.
transfer-learning ellipsis german-language t5 llm t5-base t5-small automatic-ellipsis-reconstruction
- Updated
- Jupyter Notebook
A RAG (Retrieval augmented generation)-based FAQ Chat-Bot, designed to operate within an organization's internal domain. - Jul 2023 - Oct 2023
chatbot query-builder question-answering chat-application faqs sentence-embeddings faqbot perplexity rag sentence-transformers t5-model t5-base perplexity-ai perplexity-api llama3
- Updated
- Jupyter Notebook
An agent-based reader view plugin for summarizing an article or web page, using Fetch.ai's uAgents framework and the t5-base integration.
- Updated
- Python
Adapting a Continually Pre-Trained T5 Model on Scientific Data to German Using Cross-Lingual Transfer
- Updated
- HTML
Improve this page
Add a description, image, and links to the t5-base topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the t5-base topic, visit your repo's landing page and select "manage topics."