mmatena / model_mergingLinks
β70Updated 3 years ago
Alternatives and similar repositories for model_merging
Users that are interested in model_merging are comparing it to the libraries listed below
Sorting:
- Source code of "Task arithmetic in the tangent space: Improved editing of pre-trained models".β102Updated 2 years ago
- AI Logging for Interpretability and Explainabilityπ¬β124Updated last year
- [NeurIPS'23] Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptorsβ77Updated 6 months ago
- β95Updated last year
- β31Updated last year
- DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models (ICLR 2024)β71Updated 9 months ago
- Test-time-training on nearest neighbors for large language modelsβ44Updated last year
- β49Updated last year
- A fast, effective data attribution method for neural networks in PyTorchβ212Updated 7 months ago
- Official repository of "Localizing Task Information for Improved Model Merging and Compression" [ICML 2024]β45Updated 8 months ago
- [NeurIPS 2023] Github repository for "Composing Parameter-Efficient Modules with Arithmetic Operations"β61Updated last year
- A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity.β74Updated 4 months ago
- This is the repository for "Model Merging by Uncertainty-Based Gradient Matching", ICLR 2024.β28Updated last year
- β49Updated last year
- β43Updated last year
- Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning [ICML 2024]β17Updated last year
- β183Updated last year
- Code release for Dataless Knowledge Fusion by Merging Weights of Language Models (https://openreview.net/forum?id=FCnohuR6AnM)β89Updated last year
- `dattri` is a PyTorch library for developing, benchmarking, and deploying efficient data attribution algorithms.β78Updated last month
- β29Updated last year
- AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.β86Updated 8 months ago
- β35Updated 6 months ago
- Bayesian low-rank adaptation for large language modelsβ23Updated last year
- β35Updated last year
- [ICLR'25 Spotlight] Min-K%++: Improved baseline for detecting pre-training data of LLMsβ39Updated last month
- β93Updated last year
- β38Updated last year
- LoFiT: Localized Fine-tuning on LLM Representationsβ39Updated 6 months ago
- A Kernel-Based View of Language Model Fine-Tuning https://arxiv.org/abs/2210.05643β76Updated last year
- Code accompanying the paper "Massive Activations in Large Language Models"β169Updated last year