Arenaa / Accelerated-Generation-Techniques
This repository contains papers for a comprehensive survey on accelerated generation techniques in Large Language Models (LLMs).
☆12Updated 8 months ago
Alternatives and similar repositories for Accelerated-Generation-Techniques:
Users that are interested in Accelerated-Generation-Techniques are comparing it to the libraries listed below
- Codebase for Instruction Following without Instruction Tuning☆33Updated 4 months ago
- Official implementation of the paper: "A deeper look at depth pruning of LLMs"☆14Updated 6 months ago
- Official implementation of the ICML 2024 paper RoSA (Robust Adaptation)☆38Updated last year
- AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers☆42Updated 2 years ago
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆48Updated last year
- [NeurIPS 2024 Spotlight] Code and data for the paper "Finding Transformer Circuits with Edge Pruning".☆46Updated 2 months ago
- SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference☆40Updated 3 months ago
- [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models☆28Updated 8 months ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆25Updated 11 months ago
- The official implementation of paper: SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction.☆42Updated 4 months ago
- ☆64Updated 2 weeks ago
- ☆14Updated last year
- Code for "Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes"☆27Updated 10 months ago
- HGRN2: Gated Linear RNNs with State Expansion☆52Updated 6 months ago
- The code and data for the paper JiuZhang3.0☆40Updated 8 months ago
- BESA is a differentiable weight pruning technique for large language models.☆14Updated 11 months ago
- ☆14Updated last year
- [NeurIPS 2024] A Novel Rank-Based Metric for Evaluating Large Language Models☆40Updated 3 months ago
- Implementation of IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs (ICLR 2024).☆22Updated 8 months ago
- [ACL 2024] RelayAttention for Efficient Large Language Model Serving with Long System Prompts☆38Updated 11 months ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆32Updated 8 months ago
- An unofficial implementation of "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆35Updated 8 months ago
- [NeurIPS-2024] 📈 Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies https://arxiv.org/abs/2407.13623☆77Updated 4 months ago
- Implementation of the paper: "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆81Updated last week
- The source code of "Merging Experts into One: Improving Computational Efficiency of Mixture of Experts (EMNLP 2023)":☆35Updated 10 months ago
- From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. Ajay Jaiswal, Lu Yin, Zhenyu Zhang, Shiwei Liu,…☆42Updated 7 months ago
- ☆36Updated 5 months ago
- [NeurIPS 2024 Main Track] Code for the paper titled "Instruction Tuning With Loss Over Instructions"☆35Updated 8 months ago