Alternatives and similar repositories for ml-upscale

Users that are interested in ml-upscale are comparing it to the libraries listed below

• apple / ml-vision-transformers-ane
  ☆87Updated last year
• vladimir-chernykh / coreml-performance
  Utility to test the performance of CoreML models.
  ☆70Updated 5 years ago
• apple / ml-dr
  A light-weight implementation of ICCV2023 paper "Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Rei…
  ☆79Updated last year
• apple / ml-batchquant
  ☆22Updated 2 years ago
• apple / ml-fct
  Research publication code for "Forward Compatible Training for Large-Scale Embedding Retrieval Systems", CVPR 2022, and "FastFill: Effici…
  ☆56Updated 2 years ago
• apple / ml-spin
  This repository contains the official implementation for the ECCV'22 paper, "SPIN: An Empirical Evaluation on Sharing Parameters of Isotr…
  ☆20Updated last year
• facebookresearch / DepthShrinker
  [ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan …
  ☆72Updated 3 years ago
• apple / ml-tune-mode-convbn
  Tune-Mode ConvBN Blocks For Efficient Transfer Learning
  ☆17Updated 2 years ago
• apple / learning-compressible-subspaces
  ☆19Updated 3 years ago
• facebookresearch / DeltaCNN
  DeltaCNN End-to-End CNN Inference of Sparse Frame Differences in Videos
  ☆59Updated 2 years ago
• ziplab / EcoFormer
  [NeurIPS 2022 Spotlight] This is the official PyTorch implementation of "EcoFormer: Energy-Saving Attention with Linear Complexity"
  ☆74Updated 2 years ago
• apple / ml-quant
  Research publication code for "Least Squares Binary Quantization of Neural Networks"
  ☆83Updated 2 years ago
• meta-pytorch / superblock
  A block oriented training approach for inference time optimization.
  ☆34Updated last year
• snap-research / efficient-nn-tutorial
  Page for the CVPR 2023 Tutorial - Efficient Neural Networks: From Algorithm Design to Practical Mobile Deployments
  ☆12Updated 2 years ago
• VITA-Group / AsViT
  [ICLR 2022] "As-ViT: Auto-scaling Vision Transformers without Training" by Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wa…
  ☆76Updated 3 years ago
• NVlabs / EfficientDL
  ☆33Updated 2 months ago
• DeadAt0m / LSQFakeQuantize-PyTorch
  FakeQuantize with Learned Step Size(LSQ+) as Observer in PyTorch
  ☆34Updated 3 years ago
• NVlabs / HALP
  ☆68Updated 2 years ago
• RangiLyu / llama.mmengine
  Training LLaMA language model with MMEngine! It supports LoRA fine-tuning!
  ☆41Updated 2 years ago
• tianyic / only_train_once_personal_footprint
  OTOv1-v3, NeurIPS, ICLR, TMLR, DNN Training, Compression, Structured Pruning, Erasing Operators, CNN, Diffusion, LLM
  ☆309Updated 11 months ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆34Updated 2 years ago
• IntelLabs / DyNAS-T
  Dynamic Neural Architecture Search Toolkit
  ☆30Updated 8 months ago
• NVlabs / SMCP
  ☆22Updated 2 years ago
• snap-research / F8Net
  [ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization
  ☆95Updated 3 years ago
• IBM / qattn
  Efficient GPU kernels for mixed-precision Vision Transformers in Triton
  ☆15Updated 3 months ago
• facebookresearch / NASViT
  code for NASViT
  ☆66Updated 3 years ago
• OscarXZQ / weight-selection
  ☆182Updated 11 months ago
• alenic / timm-models-explorer
  Timm model explorer
  ☆41Updated last year
• VITA-Group / Random_Pruning
  [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…
  ☆75Updated 2 years ago
• Qualcomm-AI-research / transformer-quantization
  ☆206Updated 3 years ago