apple / ml-batchquant
☆20Updated 2 years ago
Alternatives and similar repositories for ml-batchquant:
Users that are interested in ml-batchquant are comparing it to the libraries listed below
- This repository contains the official implementation for the ECCV'22 paper, "SPIN: An Empirical Evaluation on Sharing Parameters of Isotr…☆20Updated last year
- Self-Conditioning Pre-Trained Language Models, ICML 2022☆31Updated 2 years ago
- ☆42Updated 2 years ago
- Export utility for unconstrained channel pruned models☆72Updated last year
- Tune-Mode ConvBN Blocks For Efficient Transfer Learning☆17Updated last year
- ☆19Updated 3 years ago
- Repository accompanying the Interspeech 2022 publication titled "Space-Efficient Representation of Entity-centric Query Language Models" …☆13Updated 2 years ago
- Research publication code for "Forward Compatible Training for Large-Scale Embedding Retrieval Systems", CVPR 2022, and "FastFill: Effici…☆55Updated 2 years ago
- DUET: 2D Structured and Approximately Equivariant Representations, ICML 2023☆18Updated last year
- ☆47Updated 2 years ago
- ☆11Updated last year
- ☆23Updated 3 years ago
- ☆9Updated 2 years ago
- Dynamic Neural Architecture Search Toolkit☆30Updated 5 months ago
- ☆13Updated last year
- A block oriented training approach for inference time optimization.☆33Updated 8 months ago
- ☆12Updated last year
- ☆15Updated last year
- Memory Optimizations for Deep Learning (ICML 2023)☆64Updated last year
- ☆11Updated 2 years ago
- A light-weight implementation of ICCV2023 paper "Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Rei…☆79Updated last year
- ☆29Updated last year
- This is a collection of our research on efficient AI, covering hardware-aware NAS and model compression.☆83Updated 6 months ago
- ☆82Updated last year
- ☆41Updated last year
- ☆26Updated last year
- Work in progress.☆61Updated last month
- Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs☆81Updated 5 months ago
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆36Updated 7 months ago
- See the device (CPU/GPU/ANE) and estimated cost for every layer in your CoreML model.☆22Updated 11 months ago