Alternatives and similar repositories for transformers-as-statisticians

Users that are interested in transformers-as-statisticians are comparing it to the libraries listed below

• DeqingFu / transformers-icl-second-order
  Official repository for our paper, Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Mode…
  ☆18Updated 9 months ago
• automl / is_mamba_capable_of_icl
  ☆18Updated last year
• mansheej / icl-task-diversity
  Code for the paper "Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression"
  ☆21Updated 2 years ago
• locuslab / edge-of-stability
  ☆70Updated 8 months ago
• Jiacheng-Zhu-AIML / AsymmetryLoRA
  Preprint: Asymmetry in Low-Rank Adapters of Foundation Models
  ☆35Updated last year
• IlanPrice / DCTpS
  Code for testing DCT plus Sparse (DCTpS) networks
  ☆14Updated 4 years ago
• dtsip / in-context-learning
  ☆238Updated last year
• radarFudan / Curse-of-memory
  Curse-of-memory phenomenon of RNNs in sequence modelling
  ☆19Updated 3 months ago
• cassidylaidlaw / orpo
  ☆18Updated 9 months ago
• MaximeRobeyns / bayesian_lora
  Bayesian Low-Rank Adaptation for Large Language Models
  ☆35Updated last year
• p-lambda / incontext-learning
  Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implici…
  ☆108Updated last year
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• rtaori / data_feedback
  Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"
  ☆16Updated 2 years ago
• reds-lab / LAVA
  This is an official repository for "LAVA: Data Valuation without Pre-Specified Learning Algorithms" (ICLR2023).
  ☆51Updated last year
• JeanKaddour / NoTrainNoGain
  Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)
  ☆81Updated last year
• cassidylaidlaw / hidden-context
  Code and data for the paper "Understanding Hidden Context in Preference Learning: Consequences for RLHF"
  ☆30Updated last year
• RobertCsordas / modules
  The official repository for our paper "Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks". We…
  ☆46Updated last year
• machine-discovery / deer
  Parallelizing non-linear sequential models over the sequence length
  ☆53Updated 2 months ago
• liziniu / policy_optimization
  Code for Paper (Policy Optimization in RLHF: The Impact of Out-of-preference Data)
  ☆28Updated last year
• UW-Madison-Lee-Lab / Expressive_Power_of_LoRA
  Code for "The Expressive Power of Low-Rank Adaptation".
  ☆20Updated last year
• thudzj / ELLA
  Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
  ☆16Updated 2 years ago
• r-three / mats
  ☆31Updated last year
• formll / resolving-scaling-law-discrepancies
  ☆20Updated last year
• adamxyang / laplace-lora
  Bayesian low-rank adaptation for large language models
  ☆23Updated last year
• haotiansun14 / BBox-Adapter
  Lightweight Adapting for Black-Box Large Language Models
  ☆23Updated last year
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 3 years ago
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆61Updated 2 years ago
• alexrame / rewardedsoups
  Rewarded soups official implementation
  ☆60Updated last year
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆47Updated 2 years ago
• princeton-pli / what-makes-good-rm
  What Makes a Reward Model a Good Teacher? An Optimization Perspective
  ☆36Updated 2 months ago