TianjinYellow / EdgeDeviceLLMCompetition-Starting-KitLinks
☆43Updated 11 months ago
Alternatives and similar repositories for EdgeDeviceLLMCompetition-Starting-Kit
Users that are interested in EdgeDeviceLLMCompetition-Starting-Kit are comparing it to the libraries listed below
Sorting:
- Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.☆123Updated 2 months ago
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆61Updated last year
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆80Updated 11 months ago
- Awesome list for LLM pruning.☆264Updated this week
- [ICLR‘24 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"☆95Updated 3 months ago
- A curated list of early exiting (LLM, CV, NLP, etc)☆64Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆66Updated 6 months ago
- [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models☆102Updated last year
- Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"☆72Updated 3 months ago
- Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks☆37Updated 8 months ago
- The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".☆76Updated 6 months ago
- This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs☆40Updated last year
- ☆230Updated last year
- ☆59Updated 9 months ago
- Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**☆202Updated 7 months ago
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆128Updated 2 years ago
- ☆282Updated 3 months ago
- Explorations into some recent techniques surrounding speculative decoding☆288Updated 9 months ago
- [ICLR 2025] Palu: Compressing KV-Cache with Low-Rank Projection☆142Updated 7 months ago
- ☆61Updated last year
- Unofficial implementation for the paper "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆172Updated last year
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆67Updated last year
- ☆59Updated 10 months ago
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆50Updated last year
- Code accompanying the paper "Massive Activations in Large Language Models"☆183Updated last year
- [ICML 2024] KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache☆326Updated 2 weeks ago
- ☆20Updated 10 months ago
- [NeurIPS 2024] The official implementation of "Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exitin…☆60Updated last year
- ☆51Updated last year
- [NeurIPS 24 Spotlight] MaskLLM: Learnable Semi-structured Sparsity for Large Language Models☆177Updated 9 months ago