README.md

---
title: Flan-T5-Large-Demo
emoji: 📊
colorFrom: green
colorTo: gray
sdk: gradio
sdk_version: 3.18.0
app_file: app.py
pinned: false
license: mit
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

The Flan-T5 model is a variant of the T5 (Text-to-Text Transfer Transformer) model, which is a large-scale neural network architecture designed for a wide range of natural language processing tasks, including language translation, question-answering, and summarization, among others.

The Flan-T5 model was trained on a combination of several large-scale datasets, including:

C4: The Colossal Clean Crawled Corpus - a large, multilingual dataset of web pages collected by crawling the internet, containing over 700GB of text in more than 100 languages.

Wikipedia: A dataset of text extracted from Wikipedia articles in various languages.

Common Crawl News: A dataset of news articles collected from various news sources.

BooksCorpus: A large dataset of text passages extracted from over 11,000 books, containing over 800 million words.

OpenWebText: A dataset of text scraped from web pages, similar to C4.

WebText: A smaller dataset of web pages containing around 40GB of text.

English-language books and articles from the JSTOR database.

These datasets were preprocessed and used to train the Flan-T5 model on a range of natural language processing tasks, including text classification, question-answering, and summarization, among others. The Flan-T5 model has been fine-tuned on various downstream tasks, including sentiment analysis, summarization, and language translation.