theyoungkwon / TinyTrain
The official implementation of TinyTrain [ICML '24]
☆21Updated 6 months ago
Alternatives and similar repositories for TinyTrain:
Users that are interested in TinyTrain are comparing it to the libraries listed below
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆30Updated 3 years ago
- Efficient LLM Inference Acceleration using Prompting☆46Updated 3 months ago
- A collection of research papers on efficient training of DNNs☆69Updated 2 years ago
- Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight…☆60Updated 6 months ago
- Comparison of method "Pruning at initialization prior to training" (Synflow/SNIP/GraSP) in PyTorch☆14Updated 9 months ago
- [ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark☆106Updated last year
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆32Updated last year
- [ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inferen…☆13Updated 3 years ago
- Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"☆18Updated last year
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆46Updated last year
- A curated list of early exiting (LLM, CV, NLP, etc)☆41Updated 5 months ago
- ☆25Updated 3 years ago
- ☆74Updated 2 years ago
- ☆43Updated last year
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆30Updated 2 years ago
- Official implementation of Neurips 2020 "Sparse Weight Activation Training" paper.☆27Updated 3 years ago
- Measuring and predicting on-device metrics (latency, power, etc.) of machine learning models☆66Updated last year
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 2 years ago
- ☆49Updated last year
- ☆20Updated 11 months ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆58Updated last year
- ☆41Updated this week
- [ICML 2023] This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binar…☆54Updated 11 months ago
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆57Updated 11 months ago
- [ICML 2022] "Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets" by Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wa…☆32Updated last year
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs☆95Updated last month
- In progress.☆63Updated 10 months ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆30Updated 5 months ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago