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GitHub topics: scaling-laws

Qingrenn/TSFM-ScalingLaws

[ICLR 2025] Official implementation of "Towards Neural Scaling Laws for Time Series Foundation Models"

Language: Jupyter Notebook - Size: 546 KB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 7 - Forks: 1

whucs21Mzy/Model-Hemorrhage

Model Hemorrhage and the Robustness Limits of Large Language Models: A Perspective

Size: 775 KB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 1 - Forks: 0

huggingface/datablations

Scaling Data-Constrained Language Models

Language: Jupyter Notebook - Size: 43.4 MB - Last synced at: 9 days ago - Pushed at: 7 months ago - Stars: 335 - Forks: 19

kyo-takano/chinchilla

A toolkit for scaling law research ⚖

Language: Python - Size: 6.68 MB - Last synced at: 13 days ago - Pushed at: 3 months ago - Stars: 49 - Forks: 4

jialuechen/pytca

Python Library for Transaction Cost Analysis and Market Simulation

Language: Python - Size: 26.9 MB - Last synced at: 17 days ago - Pushed at: 3 months ago - Stars: 137 - Forks: 6

machinelearningnuremberg/DPL

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

Language: Python - Size: 13.7 MB - Last synced at: 7 days ago - Pushed at: over 1 year ago - Stars: 15 - Forks: 3

KomeijiForce/Cuckoo

Cuckoo: A Series of IE Free Riders Using LLM's Resources to Scale up Themselves.

Language: Python - Size: 248 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 7 - Forks: 0

linhaowei1/Fine-tuning-Scaling-Law

🌹[ICML 2024] Selecting Large Language Model to Fine-tune via Rectified Scaling Law

Language: Python - Size: 5.04 MB - Last synced at: 15 days ago - Pushed at: about 2 months ago - Stars: 3 - Forks: 0

supersimple33/Scaling-Laws

A method for calculating scaling laws for LLMs from publicly available models

Language: Python - Size: 469 KB - Last synced at: 1 day ago - Pushed at: 12 months ago - Stars: 9 - Forks: 0

PV-Bhat/RSRC

RSRC Calculator is a practical tool designed to evaluate the efficiency of AI models in the post-scaling era: Recursive Self-Referential Compression (RSRC), this tool computes training efficiency metrics by analyzing factors such as training FLOPs, energy consumption, and model architecture details.

Language: Python - Size: 75.2 KB - Last synced at: about 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

benjaminnNgo/ScalingTGNs

Language: Python - Size: 265 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 7 - Forks: 0

VITA-Group/Data-Efficient-Scaling

[ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang

Language: Python - Size: 188 KB - Last synced at: about 21 hours ago - Pushed at: over 1 year ago - Stars: 14 - Forks: 0

jennynzhuang/LLM_Scaling_Laws

Presentation on Scaling Laws for Neural Language Models​

Language: Jupyter Notebook - Size: 1.51 MB - Last synced at: 25 days ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

wiifly/GhostCities

This is a repository containing the code, data, and visulizations that I made as a part of my senior capstone project

Language: Jupyter Notebook - Size: 37.3 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

CJReinforce/JOWA

Official code for the paper, "Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining"

Language: Python - Size: 97 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 10 - Forks: 0

SLAMPAI/large-scale-pretraining-transfer

Code for reproducing the experiments on large-scale pre-training and transfer learning for the paper "Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images" (https://arxiv.org/abs/2106.00116)

Language: Jupyter Notebook - Size: 401 KB - Last synced at: 5 months ago - Pushed at: almost 3 years ago - Stars: 18 - Forks: 4

ArlindKadra/DPL

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

Language: Python - Size: 13.7 MB - Last synced at: 8 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

tanaydesai/scaling-laws

Scaling laws web calculator to get a model's training compute flops, costs and energy utilization.

Language: JavaScript - Size: 355 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

LAION-AI/scaling-laws-openclip

Reproducible scaling laws for contrastive language-image learning (https://arxiv.org/abs/2212.07143)

Language: Jupyter Notebook - Size: 1.44 MB - Last synced at: 11 months ago - Pushed at: over 1 year ago - Stars: 135 - Forks: 11

christinakim/scaling-laws-for-language-transfer

code for Scaling Laws for Language Transfer Learning

Language: Python - Size: 19.7 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 6 - Forks: 1

upunaprosk/small-language-models

Code for CoNLL BabyLM workshop Mini Minds: Exploring Bebeshka and Zlata Baby Models

Language: Jupyter Notebook - Size: 72.3 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

xiaoyuxie-vico/PyDimension

Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurements".

Language: Jupyter Notebook - Size: 5.72 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 20 - Forks: 4

Related Keywords
scaling-laws 22 deep-learning 9 machine-learning 7 llm 4 large-language-models 4 fine-tuning 3 language-model 3 pytorch 3 transfer-learning 3 pretraining 2 reinforcement-learning 2 transformers 2 hpo 2 hyperparameter-optimization 2 pre-training 2 pre-trained-model 2 transformer 2 ai 2 few-shot-learning 2 nlp 2 quantization 2 llms 2 mimic-cxr 1 medical-imaging 1 large-scale-learning 1 physics-informed 1 imagenet 1 scientific-machine-learning 1 system-identification 1 distributed-training 1 covidx-dataset 1 chexpert-dataset 1 chest-xray-images 1 chest-x-ray14 1 big-transfer 1 world-model 1 few-shot 1 atari 1 natural-language-processing 1 pytorch-lightning 1 openai 1 huggingface-transformers 1 zero-shot-retrieval 1 zero-shot-classification 1 openclip 1 laion 1 clip 1 gpt-2 1 graphcore 1 multi-fidelity 1 learning-curve-prediction 1 ipu 1 supercomputing 1 roberta 1 manufacturing 1 partial-differential-equations 1 padchest-dataset 1 mlp 1 hyperparameter-tuning 1 computer-vision 1 benchmark 1 what-if-analysis 1 price-impact 1 order-flow 1 market-microstructure 1 best-execution 1 algorithmic-trading 1 flops 1 language-models 1 high-performance-computing 1 gpt 1 robustness 1 pruning-optimization 1 normalization 1 moe 1 decoding 1 time-series 1 artificial-intelligence 1 visualization 1 gis 1 geopandas 1 dask 1 transformers-models 1 neural-language-model 1 model-reusing 1 data-efficient 1 temporal-graph-neu 1 foundation-models 1 rsrc 1 mixture-of-experts 1 model-selection 1 fine-tune 1 information-extraction 1 cuckoo 1 tabular-data 1 power-laws 1 neurips-2023 1 neurips 1