OscarXZQ / weight-selectionLinks
☆180Updated 9 months ago
Alternatives and similar repositories for weight-selection
Users that are interested in weight-selection are comparing it to the libraries listed below
Sorting:
- Official code for "TOAST: Transfer Learning via Attention Steering"☆189Updated last year
- Official code for our CVPR'22 paper “Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space”☆250Updated last year
- Implementation of Soft MoE, proposed by Brain's Vision team, in Pytorch☆304Updated 3 months ago
- Matryoshka Multimodal Models☆111Updated 5 months ago
- ☆51Updated last year
- Code for experiments for "ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy"☆101Updated 10 months ago
- [CVPR'24 Highlight] PyTorch Implementation of Object Recognition as Next Token Prediction☆180Updated 2 months ago
- [CVPR 2025 Highlight] The official CLIP training codebase of Inf-CL: "Breaking the Memory Barrier: Near Infinite Batch Size Scaling for C…☆260Updated 5 months ago
- Official implementation of "DoRA: Weight-Decomposed Low-Rank Adaptation"☆124Updated last year
- A repository for DenseSSMs☆87Updated last year
- [ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.☆103Updated 6 months ago
- Implementation of the paper: "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆99Updated last week
- Code for NOLA, an implementation of "nola: Compressing LoRA using Linear Combination of Random Basis"☆56Updated 10 months ago
- 1.5−3.0× lossless training or pre-training speedup. An off-the-shelf, easy-to-implement algorithm for the efficient training of foundatio…☆221Updated 10 months ago
- Official code for our paper, "LoRA-Pro: Are Low-Rank Adapters Properly Optimized? "☆126Updated 3 months ago
- PyTorch implementation of Soft MoE by Google Brain in "From Sparse to Soft Mixtures of Experts" (https://arxiv.org/pdf/2308.00951.pdf)☆74Updated last year
- A framework for merging models solving different tasks with different initializations into one multi-task model without any additional tr…☆301Updated last year
- Are gradient information useful for pruning of LLMs?☆46Updated last year
- A simple minimal implementation of Reversible Vision Transformers☆125Updated last year
- Official implementation of AAAI 2023 paper "Parameter-efficient Model Adaptation for Vision Transformers"☆104Updated last year
- Official repository for the paper "SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention"☆98Updated 9 months ago
- Implementation of MaMMUT, a simple vision-encoder text-decoder architecture for multimodal tasks from Google, in Pytorch☆103Updated last year
- ☆115Updated 11 months ago
- [ICML 2024] This repository includes the official implementation of our paper "Rejuvenating image-GPT as Strong Visual Representation Lea…☆98Updated last year
- Reproducible scaling laws for contrastive language-image learning (https://arxiv.org/abs/2212.07143)☆169Updated 3 weeks ago
- [CVPR'24] Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities☆99Updated last year
- When do we not need larger vision models?☆400Updated 5 months ago
- [ICLR 2025] Official PyTorch implementation of "Forgetting Transformer: Softmax Attention with a Forget Gate"☆115Updated last week
- [NeurIPS 2024] Official Repository of The Mamba in the Llama: Distilling and Accelerating Hybrid Models☆222Updated 2 months ago
- ☆50Updated 5 months ago