ykwon0407

ykwon0407's Stars

• chenfei-wu/TaskMatrix

  Language:Python34.6k3013553.3k

• tatsu-lab/stanford_alpaca

  Code and documentation to train Stanford's Alpaca models, and generate the data.

  Language:Python29.6k3422684.1k

• AI4Finance-Foundation/FinGPT

  FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

  Language:Jupyter Notebook14.1k2571052k

• faridrashidi/kaggle-solutions

  🏅 Collection of Kaggle Solutions and Ideas 🏅

  Language:HTML5k8781.9k

• google-research/timesfm

  TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

  Language:Python3.8k38119328

• Luodian/Otter

  🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.

  Language:Python3.6k100163243

• Zjh-819/LLMDataHub

  A quick guide (especially) for trending instruction finetuning datasets

  2.7k503171

• Nixtla/nixtla

  TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

  Language:Jupyter Notebook2.4k36165192

• EleutherAI/pythia

  The hub for EleutherAI's work on interpretability and learning dynamics

  Language:Jupyter Notebook2.3k33109173

• EleutherAI/the-pile

  Language:Python1.5k30100128

• Weixin-Liang/LLM-scientific-feedback

  Can large language models provide useful feedback on research papers? A large-scale empirical analysis.

  Language:Python49942648

• lm-sys/llm-decontaminator

  Code for the paper "Rethinking Benchmark and Contamination for Language Models with Rephrased Samples"

  Language:Python2943623

• HazyResearch/TART

  TART: A plug-and-play Transformer module for task-agnostic reasoning

  Language:Python19020215

• opendataval/opendataval

  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)

  Language:Python882188

• alstonlo/torch-influence

  A simple PyTorch implementation of influence functions.

  Language:Python8031111

• centerforaisafety/Intro_to_ML_Safety

  654019

• ykwon0407/DataInf

  DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models (ICLR 2024)

  Language:Jupyter Notebook55147

• wagner-d/TimeSeAD

  Language:Python44278

• reds-lab/LAVA

  This is an official repository for "LAVA: Data Valuation without Pre-Specified Learning Algorithms" (ICLR2023).

  Language:Python43028

• samuel-yeom/ml-privacy-csf18

  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"

  Language:Python38535

• Rowan1224/FakeNews

  Language:Python345213

• uvanlp/valda

  A Python Data Valuation Package

  Language:Python28214

• jjbrophy47/tree_influence

  Influence Estimation for Gradient-Boosted Decision Trees

  Language:Python254410

• mikeybellissimo/LoRA-MPT

  A repo for finetuning MPT using LoRA. It is currently configured to work with the Alpaca dataset from Stanford but can easily be adapted to use another.

  Language:Jupyter Notebook18197

• BrachioLab/incontext_influences

  In-context Example Selection with Influences

  Language:Python14211

• yuhui-zh15/NeQA

  Official Code Release for "Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models" (ACL 2023 Findings)

  Language:Jupyter Notebook9100

• yzhang511/TimeInf

  Time series data contribution via influence functions

  Language:Python8300

• linamy85/arxiv-crawler

  Arxiv crawler (only abstract)

  Language:Python4204

• reds-lab/2d-shapley

  This is an official repository for "2D-Shapley: A Framework for Fragmented Data Valuation" (ICML2023).

  Language:Jupyter Notebook4011

• opendataval/opendataval.github.io

  opendataval documentation

  Language:HTML3101