Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.

Toolkit for fine-tuning, ablating and unit-testing open-source LLMs.

This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.

[Preprint] Learning to Filter Context for Retrieval-Augmented Generaton

Official implementation of the paper "CoEdIT: Text Editing by Task-Specific Instruction Tuning" (EMNLP 2023)

LLMs4OL:‌ Large Language Models for Ontology Learning

This repository contains the code to train flan t5 with alpaca instructions and low rank adaptation.

Rethinking Negative Instances for Generative Named Entity Recognition

Empower your LLM to do more than you ever thought possible with these state-of-the-art prompt templates.

Fine-tuning of Flan-5T LLM for text classification

Tools and our test data developed for the HackAPrompt 2023 competition

A template Next.js app for running language models like FLAN-T5 with Replicate's API

Use AI to personify books, so that you can talk to them 🙊

The TABLET benchmark for evaluating instruction learning with LLMs for tabular prediction.

In this implementation, using the Flan T5 large language model, we performed the Text Classification task on the IMDB dataset and obtained a very good accuracy of 93%.

Training and fine-tuning flan-t5-small model based on provided text

In-context learning, Fine-Tuning, RLHF on Flan-T5

Document Summarization App using large language model (LLM) and Langchain framework. Used a pre-trained T5 model and its tokenizer from Hugging Face Transformers library. Created a summarization pipeline to generate summary using model.

This repository contains the lab work for Coursera course on "Generative AI with Large Language Models".

The official fork of THoR Chain-of-Thought framework, enhanced and adapted for Emotion Cause Analysis (ECAC-2024)