Alternatives and similar repositories for hessian-spectrum:

Users that are interested in hessian-spectrum are comparing it to the libraries listed below

• locuslab / edge-of-stability
  ☆63Updated 2 months ago
• JonasGeiping / linear_cross_entropy_loss
  A fusion of a linear layer and a cross entropy loss, written for pytorch in triton.
  ☆62Updated 6 months ago
• gortizji / tangent_task_arithmetic
  Source code of "Task arithmetic in the tangent space: Improved editing of pre-trained models".
  ☆94Updated last year
• tml-epfl / why-weight-decay
  Why Do We Need Weight Decay in Modern Deep Learning? [NeurIPS 2024]
  ☆60Updated 4 months ago
• JeanKaddour / NoTrainNoGain
  Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)
  ☆79Updated last year
• ZO-Bench / ZO-LLM
  [ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".
  ☆86Updated 7 months ago
• berlino / seq_icl
  ☆51Updated 9 months ago
• epfml / schedules-and-scaling
  Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"
  ☆70Updated 3 months ago
• WeiHuang05 / Awesome_Large_Foundation_Model_Theory
  Welcome to the 'In Context Learning Theory' Reading Group
  ☆28Updated 3 months ago
• locuslab / massive-activations
  Code accompanying the paper "Massive Activations in Large Language Models"
  ☆140Updated 11 months ago
• andyjm3 / SLTrain
  SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining (NeurIPS 2024)
  ☆30Updated 3 months ago
• gregorbachmann / Next-Token-Failures
  ☆80Updated 11 months ago
• epfml / llm-baselines
  nanoGPT-like codebase for LLM training
  ☆89Updated this week
• Leiay / looped_transformer
  ☆23Updated last year
• shawntan / stickbreaking-attention
  Stick-breaking attention
  ☆43Updated last month
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆56Updated last year
• lzhangbv / eva
  [ICLR 2023] Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation
  ☆12Updated last year
• VITA-Group / Junk_DNA_Hypothesis
  [ICML 2024] Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity; Lu Yin*, Ajay Jaiswal*, Shiwei Liu, So…
  ☆16Updated 8 months ago
• allenbai01 / transformers-as-statisticians
  ☆28Updated last year
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• insuhan / hyper-attn
  ☆77Updated last year
• ryoungj / ObsScaling
  [NeurIPS'24 Spotlight] Observational Scaling Laws
  ☆50Updated 4 months ago
• epfml / REQ
  ☆17Updated 8 months ago
• hendrydong / NTK-and-MF-examples
  Visualization of mean field and neural tangent kernel regime
  ☆21Updated 6 months ago
• ldery / Bonsai
  Code for "Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes"
  ☆27Updated 10 months ago
• Jiacheng-Zhu-AIML / AsymmetryLoRA
  Preprint: Asymmetry in Low-Rank Adapters of Foundation Models
  ☆34Updated 11 months ago
• igul222 / plaid
  ☆86Updated last year
• VITA-Group / Random-MoE-as-Dropout
  [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…
  ☆48Updated last year
• shikaiqiu / compute-better-spent
  ☆52Updated 4 months ago
• mueller-mp / SAM-ON
  ☆34Updated last year