mit-han-lab / offsite-tuning

Related projects ⓘ

Alternatives and complementary repositories for offsite-tuning

• sail-sg / lorahub
  [COLM 2024] LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition
  ☆587Updated 3 months ago
• JayZhang42 / FederatedGPT-Shepherd
  Shepherd: A foundational framework enabling federated instruction tuning for large language models
  ☆202Updated last year
• p-lambda / dsir
  DSIR large-scale data selection framework for language model training
  ☆227Updated 7 months ago
• locuslab / wanda
  A simple and effective LLM pruning approach.
  ☆660Updated 3 months ago
• neelsjain / NEFTune
  Official repository of NEFTune: Noisy Embeddings Improves Instruction Finetuning
  ☆381Updated 5 months ago
• huggingface / datablations
  Scaling Data-Constrained Language Models
  ☆321Updated last month
• Shark-NLP / OpenICL
  OpenICL is an open-source framework to facilitate research, development, and prototyping of in-context learning.
  ☆535Updated last year
• yuhuixu1993 / qa-lora
  Official PyTorch implementation of QA-LoRA
  ☆116Updated 7 months ago
• prateeky2806 / ties-merging
  ☆149Updated 9 months ago
• yxli2123 / LoftQ
  ☆197Updated 4 months ago
• declare-lab / instruct-eval
  This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.
  ☆528Updated 8 months ago
• benzakenelad / BitFit
  Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models
  ☆133Updated 2 years ago
• mlfoundations / task_vectors
  Editing Models with Task Arithmetic
  ☆425Updated 9 months ago
• QingruZhang / AdaLoRA
  AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (ICLR 2023).
  ☆269Updated last year
• lucidrains / speculative-decoding
  Explorations into some recent techniques surrounding speculative decoding
  ☆209Updated last year
• EnnengYang / Awesome-Model-Merging-Methods-Theories-Applications
  Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
  ☆204Updated this week
• AGI-Edgerunners / LLM-Adapters
  Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"
  ☆1,074Updated 8 months ago
• sangmichaelxie / doremi
  Pytorch implementation of DoReMi, a method for optimizing the data mixture weights in language modeling datasets
  ☆304Updated 10 months ago
• princeton-nlp / LLM-Shearing
  [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
  ☆553Updated 8 months ago
• locuslab / massive-activations
  Code accompanying the paper "Massive Activations in Large Language Models"
  ☆121Updated 8 months ago
• WoosukKwon / retraining-free-pruning
  [NeurIPS 2022] A Fast Post-Training Pruning Framework for Transformers
  ☆167Updated last year
• for-ai / parameter-efficient-moe
  ☆246Updated last year
• r-three / t-few
  Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"
  ☆430Updated last year
• llm-efficiency-challenge / neurips_llm_efficiency_challenge
  NeurIPS Large Language Model Efficiency Challenge: 1 LLM + 1GPU + 1Day
  ☆251Updated last year
• OpenNLPLab / TransnormerLLM
  Official implementation of TransNormerLLM: A Faster and Better LLM
  ☆229Updated 9 months ago
• lm-sys / llm-decontaminator
  Code for the paper "Rethinking Benchmark and Contamination for Language Models with Rephrased Samples"
  ☆292Updated 10 months ago
• princeton-nlp / CoFiPruning
  [ACL 2022] Structured Pruning Learns Compact and Accurate Models https://arxiv.org/abs/2204.00408
  ☆191Updated last year
• pprp / Awesome-LLM-Prune
  Awesome list for LLM pruning.
  ☆159Updated last month
• CASE-Lab-UMD / LLM-Drop
  The official implementation of the paper "What Matters in Transformers? Not All Attention is Needed".
  ☆120Updated 2 weeks ago
• UIC-Liu-Lab / ContinualLM
  An Extensible Continual Learning Framework Focused on Language Models (LMs)
  ☆250Updated 9 months ago