Alternatives and similar repositories for edge-qat:

Users that are interested in edge-qat are comparing it to the libraries listed below

• htqin / IR-QLoRA
  [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…
  ☆60Updated 9 months ago
• zyxxmu / DSnoT
  Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…
  ☆38Updated 9 months ago
• CASIA-IVA-Lab / FLAP
  [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models
  ☆40Updated last year
• SempraETY / Pruning-via-Merging
  ☆16Updated last month
• HuangOwen / RoLoRA
  [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization
  ☆27Updated 3 months ago
• lliai / Awesome-LoRA-Low-Rank-Adaptation
  Awesome-Low-Rank-Adaptation
  ☆62Updated 3 months ago
• Intelligent-Computing-Lab-Yale / TesseraQ
  ☆18Updated 2 months ago
• yxli2123 / LoSparse
  ☆49Updated last year
• VILA-Lab / GBLM-Pruner
  Are gradient information useful for pruning of LLMs?
  ☆41Updated 8 months ago
• nbasyl / OFQ
  The official implementation of the ICML 2023 paper OFQ-ViT
  ☆30Updated last year
• ThisisBillhe / EfficientDM
  [ICLR 2024 Spotlight] This is the official PyTorch implementation of "EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Di…
  ☆55Updated 7 months ago
• ldery / Bonsai
  Code for "Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes"
  ☆27Updated 9 months ago
• aiha-lab / MX-QLLM
  LLM Inference with Microscaling Format
  ☆16Updated 2 months ago
• BaiTheBest / SparseLLM
  Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)
  ☆51Updated 3 weeks ago
• ROIM1998 / APT
  [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
  ☆31Updated 7 months ago
• raymin0223 / fast_robust_early_exit
  Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding (EMNLP 2023 Long)
  ☆56Updated 3 months ago
• xvyaward / owq
  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
• VITA-Group / Random-MoE-as-Dropout
  [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…
  ☆48Updated last year
• Qualcomm-AI-research / lr-qat
  ☆26Updated 2 months ago
• Qualcomm-AI-research / outlier-free-transformers
  ☆39Updated last year
• wimh966 / outlier_suppression
  The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…
  ☆47Updated 2 years ago
• ChenMnZ / PrefixQuant
  An algorithm for static activation quantization of LLMs
  ☆107Updated last week
• ruikangliu / IntactKV
  Official PyTorch implementation of IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact
  ☆38Updated 7 months ago
• sanagno / adaptively_sparse_attention
  ☆18Updated last year
• yifanycc / loretta
  [NAACL 24 Oral] LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
  ☆33Updated last week
• ylsung / ECoFLaP
  Code for "ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models" (ICLR 2024)
  ☆18Updated 11 months ago
• hahnyuan / ASVD4LLM
  Activation-aware Singular Value Decomposition for Compressing Large Language Models
  ☆55Updated 2 months ago
• OpenGVLab / LLMPrune-BESA
  BESA is a differentiable weight pruning technique for large language models.
  ☆14Updated 10 months ago
• zhangsichengsjtu / AFPQ
  AFPQ code implementation
  ☆19Updated last year
• ClubieDong / QAQ-KVCacheQuantization
  QAQ: Quality Adaptive Quantization for LLM KV Cache
  ☆44Updated 9 months ago