Python Fine-tuning Resources

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

KerasTuner KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily c

AttnGAN Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative

Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our

Child-Tuning Source code for EMNLP 2021 Long paper: Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning. 1. Environ

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for

The Curious Layperson: Fine-Grained Image Recognition without Expert Labels Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi Code

Overview This repository provides the implementation for the paper "Improved Regularization and Robustness for Fine-tuning in Neural Networks", which

Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe

Introduction Datasets and source code for our paper Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach Datasets: WebFG-496

Prefix Tuning Note: 作者在论文中提到使用真实的word去初始化prefix的操作（Initializing the prefix with activations of real words，significantly improves generation）。我在使用作者提供的

Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification

An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea

DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning

DSEE Codes for [Preprint] DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Ch

HA-in-Fine-Grained-Classification This repo includes the CUB-GHA (Gaze-based Human Attention) dataset and code of the paper "Human Attention in Fine-g

CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration (NeurIPS 2021) PyTorch implementation of the paper: CoFiNet: Reli

Google Chat GPT-3 This repo will help you fine-tune GPT-3 with a Google Chat conversation history. The trained model will be able to converse as one o

A Comprehensive Experimental Evaluation for Database Configuration Tuning This is the source code to the paper "Facilitating Database Tuning with Hype

PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"

Example Of Fine-Tuning BERT For Named-Entity Recognition Task And Preparing For Cloud Deployment Using Flask, React, And Docker This repository contai

Core-tuning This repository is the official implementation of ``Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regular

KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme

Cartoon-StyleGAN 🙃 : Fine-tuning StyleGAN2 for Cartoon Face Generation Abstract Recent studies have shown remarkable success in the unsupervised imag

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks

Prefix Tuning Files: . ├── gpt2 # Code for GPT2 style autoregressive LM │ ├── train_e2e.py # high-level script

MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation [Paper] Yuheng Li, Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Le

Web Scraping, Document Deduplication & GPT-2 Fine-tuning with a newly created scam dataset.

Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-safe fashion.

P-tuning v2 P-Tuning v2: Prompt Tuning Can Be Comparable to Finetuning Universally Across Scales and Tasks An optimized prompt tuning strategy for sma

N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras Official PyTorch implementation of N-ImageNet: Towards Robust, Fine-Gra

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

This is a library for training and applying sparse fine-tunings with torch and transformers. Please refer to our paper Composable Sparse Fine-Tuning f

LST-TTS Official implementation for the paper Fine-grained style control in transformer-based text-to-speech synthesis. Submitted to ICASSP 2022. Audi

Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification Suncheng Xiang Shanghai Jiao Tong University Over

Legged Robots that Keep on Learning Official codebase for Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World, whic

p-tuning_NLU Overview 这个小项目是受乐于分享的苏剑林大佬这篇p-tuning 文章启发，也实现了个使用P-tuning进行NLU分类的任务， 思路是一样的，prompt实现方式有不同，这里是将[unused*]的embeddings参数抽取出用于初始化prompt_embed后

AutoDSP TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels. About Adaptive filtering algorithms are commonplace in sign

A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.

SimTrans-Weak-Shot-Classification This repository contains the official PyTorch implementation of the following paper: Weak-shot Fine-grained Classifi

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar

Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition Currently

easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.

VehicleDetection Vehicle Detection Using Deep Learning and YOLO Algorithm Dataset take or find vehicle images for create a special dataset for fine-tu

Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV

pretrain4ir_tutorial NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking 用作NLPIR实验室, Pre-training

Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV

BanglaBERT This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced i

Pretrain and Fine-tune a T5 model with Flax on GCP This tutorial details how pretrain and fine-tune a FlaxT5 model from HuggingFace using a TPU VM ava

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu

BASNet Boundary-Aware Segmentation Network for Mobile and Web Applications This repository contain implementation of BASNet in tensorflow/keras. comme

Talk-to-Edit (ICCV2021) This repository contains the implementation of the following paper: Talk-to-Edit: Fine-Grained Facial Editing via Dialog Yumin

Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections Ruiqi Zhong, Kristy Lee*, Zheng Zhang*, Dan Klein EMN

YellowFin YellowFin is an auto-tuning optimizer based on momentum SGD which requires no manual specification of learning rate and momentum. It measure

CoTuning Official implementation for NeurIPS 2020 paper Co-Tuning for Transfer Learning. [News] 2021/01/13 The COCO 70 dataset used in the paper is av

Code for HDR Video Reconstruction HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021) Guanying Chen, Cha

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel

Stochastic CSLR This is the PyTorch implementation for the ECCV 2020 paper: Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuou

Performance Ninja Class This is an online course where you can learn to find and fix low-level performance issues, for example CPU cache misses and br

Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML). It can build custom modeling pipelines for different real-world processes in an automated way using an evolutionary approach. FEDOT supports classification (binary and multiclass), regression, clustering, and time series prediction tasks.

Temporal Query Networks for Fine-grained Video Understanding 📋 This repository contains the implementation of CVPR2021 paper Temporal_Query_Networks

Fine-tuning StyleGAN2 for Cartoon Face Generation

PTR Code and datasets for our paper "PTR: Prompt Tuning with Rules for Text Classification" If you use the code, please cite the following paper: @art

xTune Code for ACL2021 paper Consistency Regularization for Cross-Lingual Fine-Tuning. Environment DockerFile: dancingsoul/pytorch:xTune Install the f

We propose a hierarchical core-fringe learning framework to measure fine-grained domain relevance of terms – the degree that a term is relevant to a broad (e.g., computer science) or narrow (e.g., deep learning) domain.

Styleformer A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/cas

🌳 Fingerprinting Fine-tuned Language Models in the wild This is the code and dataset for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned La

GPT-Neo-2.7B Fine-Tuning Example Using HuggingFace & DeepSpeed Installation cd venv/bin ./pip install -r ../../requirements.txt ./pip install deepspe

Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic

Covid-QA Fine tuned models for question answering on Covid-19 data. Hosted Inference This model has been contributed to huggingface.Click here to see

Fine-Grained R2R Code and data of the Fine-Grained R2R Dataset proposed in the EMNLP2020 paper Sub-Instruction Aware Vision-and-Language Navigation. C

WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose Yijun Zhou and James Gregson - BMVC2020 Abstract: We present an end-to-end head-pos

OCTIS : Optimizing and Comparing Topic Models is Simple! OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and compa

Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A

P-tuning A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''. How to use our code We have released the code

LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval This repository contains source code and pre-trained/fine-tun

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

Tsinghua Dogs classification with Deep Metric Learning 1. Introduction Tsinghua Dogs dataset Tsinghua Dogs is a fine-grained classification dataset fo

Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning t

SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Supported tags and respective Dockerfile links python3.8, latest (Dockerfile) python3.7, (Dockerfile) python3.6 (Dockerfile) python3.8-slim (Dockerfil

NERDA Not only is NERDA a mesmerizing muppet-like character. NERDA is also a python package, that offers a slick easy-to-use interface for fine-tuning

C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/

Determined: Deep Learning Training Platform Determined is an open-source deep learning training platform that makes building models fast and easy. Det

MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents

Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline

Xcessiv Xcessiv is a tool to help you create the biggest, craziest, and most excessive stacked ensembles you can think of. Stacked ensembles are simpl