Python Fine-tuning Resources

🤗 🖼️ HuggingPics Fine-tune Vision Transformers for anything using images found on the web. Check out the video below for a walkthrough of this proje

T-Few This repository contains the official code for the paper: "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learni

Visual Transformer for Facial Emotion Recognition (FER) This project has the aim to build an efficient Visual Transformer for the Facial Emotion Recog

FaceVerse FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset Lizhen Wang, Zhiyuan Chen, Tao Yu, Chenguang

CaiT-TF (Going deeper with Image Transformers) This repository provides TensorFlow / Keras implementations of different CaiT [1] variants from Touvron

BIG.art: Using Machine Learning to Create High-Res Fine Art How to use GLIDE and BSRGAN to create ultra-high-resolution paintings with fine details By

ConvNeXt-TF This repository provides TensorFlow / Keras implementations of different ConvNeXt [1] variants. It also provides the TensorFlow / Keras mo

Object Detection Object detection is a computer vision task for locating instances of predefined objects in images or videos. In this tutorial, you wi

mkultra mkultra is a prompt tuning toolkit for GPT-2 and GPT-Neo. Prompt tuning injects a string of 20-100 special tokens into the context in order to

XLM-EMO: Multilingual Emotion Prediction in Social Media Text Abstract Detecting emotion in text allows social and computational scientists to study h

Seq2Seq Speech in JAX A JAX/Flax repository for combining a pre-trained speech encoder model (e.g. Wav2Vec2, HuBERT, WavLM) with a pre-trained text de

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks arXiv link: upcoming To be published in Findings of NA

P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas

Kaggle Competition: Forest Cover Type Prediction In this project we predict the forest cover type (the predominant kind of tree cover) using the carto

Transformers-for-NLP-2nd-Edition @copyright 2022, Packt Publishing, Denis Rothman Contact me for any question you have on LinkedIn Get the book on Ama

Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning This repository is official Tensorflow implementation of paper: Ensemb

On Robust Prefix-Tuning for Text Classification Prefix-tuning has drawed much attention as it is a parameter-efficient and modular alternative to adap

EntLM The source codes for EntLM. Dependencies: Cuda 10.1, python 3.6.5 To install the required packages by following commands: $ pip3 install -r requ

"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i

OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.

nerblackbox A python package to fine-tune transformer-based language models for named entity recognition (NER). Resources Source Code: https://github.

SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers This repo contains our codes for the paper "No Parameters Left Behind: Sensitivity Gu

Large-scale Knowledge Graph Construction with Prompting across tasks (predictive and generative), and modalities (language, image, vision + language, etc.)

FIRA is a learning-based commit message generation approach, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically.

Pytorch implementation for A Novel Plug-in Module for Fine-Grained Visual Classification. fine-grained visual classification task.

spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t

Plant Pathology 2020 FGVC7 Introduction A deep learning model pipeline for training, experimentaiton and deployment for the Kaggle Competition, Plant

DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment [email protected] Use pi

FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control by Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann FIGARO: Generat

UPMT Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On See main.py as an example: from model import PopM

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

FinerFact This is the PyTorch implementation for the FinerFact model in the AAAI 2022 paper Towards Fine-Grained Reasoning for Fake News Detection (Ar

EncT5 (Unofficial) Pytorch Implementation of EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks About Finetune T5 model for classification & r

package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML

github-app-user-auth Provide fine-grained push access to GitHub from a JupyterHub. Goals Allow users on a JupyterHub to grant push access to only spec

Prompt Tuning This is the code to reproduce the experiments from the EMNLP 2021 paper "The Power of Scale for Parameter-Efficient Prompt Tuning" (Lest

Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in

Applying BERT Fine Tuning to Sentiment Classification on Amazon Reviews Abstract Sentiment analysis has made great progress in recent years, due to th

FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego

Black-Box-Tuning Source code for paper "Black-Box Tuning for Language-Model-as-a-Service". Being busy recently, the code in this repo and this tutoria

Black-Box-Tuning Source code for paper "Black-Box Tuning for Language-Model-as-a

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

Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

Advisor Introduction Advisor is the hyper parameters tuning system for black box optimization. It is the open-source implementation of Google Vizier w

FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation

OCR-Pipeline-with-Keras The keras-ocr package generally consists of two parts: a Detector and a Recognizer: Detector is responsible for creating bound

mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v

Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs This repository contains PyTorch implementation of our pa

Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control.

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

Finetune AlexNet with Tensorflow Update 15.06.2016 I revised the entire code base to work with the new input pipeline coming with TensorFlow = versio

Hi, I'm Sachin Malhotra ( ⛄ 💻 🎃 🍺 ) Let me set the records straight. Roger Federer is the GOAT and I will not hear otherwise! Now that we have that

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is

Transformer-vocabulary-transfer Implementation of the paper "Fine-Tuning Transfo

A Unified Framework for Parameter-Efficient Transfer Learning This is the official implementation of the paper: Towards a Unified View of Parameter-Ef

Prompt-Tuning Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning" Currently, we support the following huggigface models: Bart

Robust fine-tuning of zero-shot models This repository contains code for the paper Robust fine-tuning of zero-shot models by Mitchell Wortsman*, Gabri

Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

ruPrompts ruPrompts is a high-level yet extensible library for fast language model tuning via automatic prompt search, featuring integration with Hugg

The KLEJ Benchmark Baselines The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language und

Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning Tensorflow code and models for the paper: Large Scale Fine-Grained Categ

Fine-grainedImageClassification Weakly Supervised Posture Mining with Reverse Cross-entropy for Fine-grained Classification We trained model here: lin

MMO: Meta Multi-Objectivization for Software Configuration Tuning This repository contains the data and code for the following paper that is currently

Larch: Data Analysis Tools for X-ray Spectroscopy and More Documentation: http://xraypy.github.io/xraylarch Code: http://github.com/xraypy/xraylarch L

Class-Balanced Loss Based on Effective Number of Samples Tensorflow code for the paper: Class-Balanced Loss Based on Effective Number of Samples Yin C

DOP-Tuning DOP-Tuning(Domain-Oriented Prefix-tuning model)代码基于Prefix-Tuning改进. Files ├── seq2seq # Code for encoder-decoder arch

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

BERTMap: A BERT-based Ontology Alignment System Important Notices The relevant paper was accepted in AAAI-2022. Arxiv version is available at: https:/

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

Fine-tuning wav2vec2 for speaker recognition This is the code used to run the experiments in https://arxiv.org/abs/2109.15053. Detailed logs of each t

AutoLRS This is the PyTorch code implementation for the paper AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly published

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

Structured Super Lottery Tickets in BERT This repo contains our codes for the paper "Super Tickets in Pre-Trained Language Models: From Model Compress

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators This is our Pytorch implementation for t

Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks This repo contains the PyTorch implementation of the ACL, 2021 pa

LM-BFF (Better Few-shot Fine-tuning of Language Models) This is the implementation of the paper Making Pre-trained Language Models Better Few-shot Lea

Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho

DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n

Public code for NIPS submission "SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement" This repo co

An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt

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

Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option

BinTuner is a cost-efficient auto-tuning framework, which can deliver a near-optimal binary code that reveals much more differences than -Ox settings. it also can assist the binary code analysis research in generating more diversified datasets for training and testing. The BinTuner framework is based on OpenTuner, thanks to all contributors for their contributions.

Faster R-CNN pretrained on VisualGenome This repository modifies maskrcnn-benchmark for object detection and attribute prediction on VisualGenome data

SSC-GAN_repo Pytorch implementation for 'Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation'.PDF SSC-GAN:Sem

KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v

Semi-Supervised Learning for Fine-Grained Classification This repo contains the code of: A Realistic Evaluation of Semi-Supervised Learning for Fine-G

fast.ai ULMFiT with SentencePiece from pretraining to deployment Motivation: Why even bother with a non-BERT / Transformer language model? Short answe

Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper par

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear