Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
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Updated
Jun 11, 2024 - Python
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
This repository collects awesome survey, resource, and paper for Lifelong Learning for Large Language Models.
This repository collects awesome survey, resource, and paper for Lifelong Learning with Large Language Models.
🌊 Online machine learning in Python
The efficient SMT-based context-bounded model checker (ESBMC)
Fwumious Wabbit, fast on-line machine learning toolkit written in Rust
In my code portfolio, I generally try new techniques and methods in machine learning. I don't like only copying and pasting.
Data Efficient Incremental Learning Via Attentive Knowledge Replay (IEEE SMC 2023)
[ACL2024] A Codebase for Incremental Learning with Large Language Models; Official released code for "Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models (ACL 2024)", "Incremental Sequence Labeling: A Tale of Two Shifts (ACL 2024 Findings)", and "Concept-1K: A Novel Benchmark for Instance Incremental Learning (arxiv)"
Code for the paper "FOCIL: Finetune-and-Freeze for Online Class-Incremental Learning by Training Randomly Pruned Sparse Experts"
PyCIL: A Python Toolbox for Class-Incremental Learning
🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox
Code for CPAL-2024 paper "Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates"
Vision-Language Large Model Incremental Learning(VLLM-IL)
An Incremental Learning, Continual Learning, and Life-Long Learning Repository
Pytorch implementation of ACCV18 paper "Revisiting Distillation and Incremental Classifier Learning."
[IJCAI 2024] Continual Multimodal Knowledge Graph Construction
Implementation of CLAD: A Continual Learning benchmark for Autonomous Driving. A continual classification and detectin track. Provides pure PyTorch, Avalanche and Detectron2 implementations.
Incremental reading card generator for Anki supporting Wikipedia & local HTML files
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