IST-DASLab / gptq
Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".
☆2,101Updated last year
Alternatives and similar repositories for gptq
Users that are interested in gptq are comparing it to the libraries listed below
Sorting:
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,401Updated 10 months ago
- [MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration☆2,991Updated this week
- AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:☆2,155Updated this week
- 4 bits quantization of LLaMA using GPTQ☆3,050Updated 10 months ago
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.☆2,009Updated last month
- Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".☆791Updated 8 months ago
- An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.☆4,838Updated last month
- Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads☆2,522Updated 10 months ago
- S-LoRA: Serving Thousands of Concurrent LoRA Adapters☆1,822Updated last year
- [ICML 2024] Break the Sequential Dependency of LLM Inference Using Lookahead Decoding☆1,246Updated 2 months ago
- A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Bla…☆2,400Updated this week
- [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization☆687Updated 9 months ago
- [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.☆805Updated 7 months ago
- Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackab…☆1,566Updated last year
- Ongoing research training transformer language models at scale, including: BERT & GPT-2☆2,066Updated last month
- A simple and effective LLM pruning approach.☆745Updated 9 months ago
- Accessible large language models via k-bit quantization for PyTorch.☆6,990Updated this week
- YaRN: Efficient Context Window Extension of Large Language Models☆1,482Updated last year
- Ongoing research training transformer language models at scale, including: BERT & GPT-2☆1,386Updated last year
- Serving multiple LoRA finetuned LLM as one☆1,060Updated last year
- [NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support Llama-3/3.1, Llama-2, LLaMA, BLOOM, Vicuna, Baich…☆1,009Updated 7 months ago
- ☆543Updated 4 months ago
- [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning☆608Updated last year
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆818Updated 8 months ago
- Official Implementation of EAGLE-1 (ICML'24), EAGLE-2 (EMNLP'24), and EAGLE-3.☆1,220Updated last week
- Automatically Discovering Fast Parallelization Strategies for Distributed Deep Neural Network Training☆1,792Updated this week
- LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalabili…☆3,202Updated this week
- A family of open-sourced Mixture-of-Experts (MoE) Large Language Models☆1,526Updated last year
- [NeurIPS 2023] MeZO: Fine-Tuning Language Models with Just Forward Passes. https://arxiv.org/abs/2305.17333☆1,104Updated last year
- The hub for EleutherAI's work on interpretability and learning dynamics☆2,476Updated last week