punica-ai / punica
Serving multiple LoRA finetuned LLM as one
☆1,058Updated last year
Alternatives and similar repositories for punica:
Users that are interested in punica are comparing it to the libraries listed below
- [ICML 2024] Break the Sequential Dependency of LLM Inference Using Lookahead Decoding☆1,246Updated 2 months ago
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆818Updated 8 months ago
- S-LoRA: Serving Thousands of Concurrent LoRA Adapters☆1,822Updated last year
- Official Implementation of EAGLE-1 (ICML'24), EAGLE-2 (EMNLP'24), and EAGLE-3.☆1,220Updated this week
- A throughput-oriented high-performance serving framework for LLMs☆805Updated last week
- [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization☆687Updated 8 months ago
- ☆531Updated 8 months ago
- [NeurIPS'24 Spotlight, ICLR'25, ICML'25] To speed up Long-context LLMs' inference, approximate and dynamic sparse calculate the attention…☆1,013Updated last week
- Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads☆2,516Updated 10 months ago
- batched loras☆342Updated last year
- Minimalistic large language model 3D-parallelism training☆1,850Updated this week
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.☆2,009Updated last month
- Memory optimization and training recipes to extrapolate language models' context length to 1 million tokens, with minimal hardware.☆723Updated 7 months ago
- The Triton TensorRT-LLM Backend☆832Updated this week
- Fast inference from large lauguage models via speculative decoding☆722Updated 8 months ago
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆663Updated 2 months ago
- Official implementation of Half-Quadratic Quantization (HQQ)☆807Updated this week
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,399Updated 10 months ago
- AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:☆2,145Updated last week
- [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning☆607Updated last year
- [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.☆805Updated 7 months ago
- Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM☆1,316Updated this week
- Large Context Attention☆709Updated 3 months ago
- YaRN: Efficient Context Window Extension of Large Language Models☆1,482Updated last year
- Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".☆2,101Updated last year
- ☆533Updated 6 months ago
- Scalable toolkit for efficient model alignment☆786Updated last week
- Latency and Memory Analysis of Transformer Models for Training and Inference☆409Updated 3 weeks ago
- Microsoft Automatic Mixed Precision Library☆595Updated 7 months ago
- [MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration☆2,991Updated this week