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Instruction fine tuning BART for Dialogue Summarization | IT4772E | NLP Project 20232
LightSeq: A High Performance Library for Sequence Processing and Generation
Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo
Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
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.
TextGen: Implementation of Text Generation models, include LLaMA, BLOOM, GPT2, BART, T5, SongNet and so on. 文本生成模型,实现了包括LLaMA,ChatGLM,BLOOM,GPT2,Seq2Seq,BART,T5,UDA等模型的训练和预测,开箱即用。
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.
Multilingual/multidomain question generation datasets, models, and python library for question generation.
Build and train state-of-the-art natural language processing models using BERT
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"