hongsunjang / pipe-bd
[DATE 2023] Pipe-BD: Pipelined Parallel Blockwise Distillation
☆11Updated last year
Alternatives and similar repositories for pipe-bd:
Users that are interested in pipe-bd are comparing it to the libraries listed below
- [HPCA'24] Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System☆39Updated 10 months ago
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆30Updated 2 years ago
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆30Updated 3 years ago
- ☆21Updated 7 months ago
- [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs☆93Updated last month
- Codebase for ICML'24 paper: Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs☆24Updated 7 months ago
- Official Implementation of "Genie: Show Me the Data for Quantization" (CVPR 2023)☆17Updated last year
- ☆39Updated last year
- Experimental deep learning framework written in Rust☆14Updated 2 years ago
- LLM Inference with Microscaling Format☆17Updated 2 months ago
- ☆31Updated 6 months ago
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆56Updated 10 months ago
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆32Updated last year
- Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight…☆60Updated 5 months ago
- [ASPLOS'23] Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression☆6Updated 5 months ago
- SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models☆26Updated 5 months ago
- ☆11Updated 3 weeks ago
- ☆15Updated 2 months ago
- Tender: Accelerating Large Language Models via Tensor Decompostion and Runtime Requantization (ISCA'24)☆13Updated 6 months ago
- ☆21Updated 2 months ago
- Official implementation for paper LIMPQ, "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance", ECCV 2022☆51Updated last year
- ☆102Updated last year
- ☆15Updated 2 years ago
- ☆48Updated 9 months ago
- ☆24Updated last year
- ☆37Updated 8 months ago
- Training-free Post-training Efficient Sub-quadratic Complexity Attention. Implemented with OpenAI Triton.☆33Updated this week
- In progress.☆64Updated 10 months ago
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆47Updated 2 years ago