shizhediao/awesome-domain-adaptation-NLP

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shizhediao/awesome-domain-adaptation-NLP

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domain adaptation in NLP

ChatGPTPapers

Must-read papers, related blogs and API tools on the pre-training and tuning methods for ChatGPT.

active-prompt

Source code for the paper "Active Prompting with Chain-of-Thought for Large Language Models"

R-Tuning

[NAACL 2024 Outstanding Paper] Source code for the NAACL 2024 paper entitled "R-Tuning: Instructing Large Language Models to Say 'I Don't Know'"

DaVinci

Source code for the paper "Prefix Language Models are Unified Modal Learners"

Jupyter Notebook

TILGAN

Source code for the Findings of ACL-IJCNLP 2021 paper entitled "TILGAN: Transformer-based Implicit Latent GAN for Diverse and Coherent Text Generation"

automate-cot

Source code for the paper "Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data"

T-DNA

Source code for the ACL-IJCNLP 2021 paper entitled "T-DNA: Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation" by Shizhe Diao et al.

BigGAN-PyTorch-TPU-Distribute

Distributed version (multiple-process) for training BigGAN with TPU.

Post-Training-Data-Flywheel

We aim to provide the best references to search, select, and synthesize high-quality and large-quantity data for post-training your LLMs.

awesome-transformers

A curated list of resources dedicated to Transformers.

HashTation

Source code for the paper "Hashtag-Guided Low-Resource Tweet Classification"

Transformers_TPU

transformers_TPU, trying to solve RAM issues with mapping dataset

BigGAN-PyTorch-TPU-Single

Single thread version for training BigGAN with TPU.

SEDST3

SEDST version 3.0 base on the Code for CIKM'18 long paper: Explicit state tracking with semi-supervision for neural dialogue generation.

Doolittle

Source code for the EMNLP 2023 paper entitled "Doolittle: Benchmarks and Corpora for Academic Writing Formalization" by Shizhe Diao et al.

BigGAN-PyTorch-TPU-Parallel

Parallel version (multiple-thread) for training BigGAN with TPU.

Black-Box-Prompt-Learning

Source code for the paper "Black-Box Prompt Learning for Pre-trained Language Models"

TPU-Tutorial

This is a tutorial for beginners who would like to use TPU with Pytorch.

MATH6450-CIFAR10

Course project for MATH6450F training two models onn CIFAR-10 to achieve a good performance. The code is adapted from CIFAR-ZOO (https://github.com/BIGBALLON/CIFAR-ZOO)