#大语言模型#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...
#自然语言处理#Toolkit for fine-tuning, ablating and unit-testing open-source LLMs.
#大语言模型#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
#自然语言处理#Official implementation of the paper "CoEdIT: Text Editing by Task-Specific Instruction Tuning" (EMNLP 2023)
#自然语言处理#Official implementation of the paper "CoEdIT: Text Editing by Task-Specific Instruction Tuning" (EMNLP 2023)
#大语言模型#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
Fine-tuning of Flan-5T LLM for text classification 🤖 focuses on adapting a state-of-the-art language model to enhance its ability to classify text data.
#大语言模型#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
#自然语言处理#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%.
#自然语言处理#Build a Large Language Model (From Scratch) book and Finetuned Models
#大语言模型#The TABLET benchmark for evaluating instruction learning with LLMs for tabular prediction.
#大语言模型#Use AI to personify books, so that you can talk to them 🙊
Training and fine-tuning flan-t5-small model based on provided text
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 pipel...
In-context learning, Fine-Tuning, RLHF on Flan-T5