tryumanshow (Seungwoo Ryu)

upvoted a collection 11 days ago

Korean Instruction Dataset

Collection

4 items • Updated 21 days ago • 4

upvoted a collection 22 days ago

MobileLLM

Collection

Optimizing Sub-billion Parameter Language Models for On-Device Use Cases (ICML 2024) https://arxiv.org/abs/2402.14905 • 8 items • Updated 16 days ago • 95

upvoted a collection about 1 month ago

Korean Reward Modeling

Collection

Korean Datasets, Reward Models for RLHF • 16 items • Updated 4 days ago • 3

upvoted a paper about 2 months ago

DiaSynth -- Synthetic Dialogue Generation Framework

Paper • 2409.19020 • Published Sep 25 • 19

upvoted an article 3 months ago

Article

The 5 Most Under-Rated Tools on Hugging Face

Aug 22

• 85

upvoted a collection 3 months ago

LLMs

Collection

303 items • Updated 1 day ago • 20

upvoted 2 papers 5 months ago

Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26 • 47

Model Merging and Safety Alignment: One Bad Model Spoils the Bunch

Paper • 2406.14563 • Published Jun 20 • 29

upvoted 4 collections 6 months ago

upvoted a paper 6 months ago

Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3

Paper • 2405.00664 • Published May 1 • 18

upvoted an article 6 months ago

Article

Mixture of Experts Explained

Dec 11, 2023

• 196

upvoted a collection 7 months ago

Long context

Collection

94 items • Updated Sep 29 • 29

upvoted an article 7 months ago

Article

Fine-tune Llama 3 with ORPO

By

•

Apr 22

• 227

upvoted a collection 7 months ago

Handbook v0.1 models and datasets

Collection

Models and datasets for v0.1 of the alignment handbook • 6 items • Updated Nov 10, 2023 • 24

Seungwoo Ryu PRO

AI & ML interests

Organizations

tryumanshow's activity

Korean Instruction Dataset

MobileLLM

Korean Reward Modeling

DiaSynth -- Synthetic Dialogue Generation Framework

The 5 Most Under-Rated Tools on Hugging Face

LLMs

Octo-planner: On-device Language Model for Planner-Action Agents

Model Merging and Safety Alignment: One Bad Model Spoils the Bunch

Function Calling v3

Agents

Miqu Models ('slerp' + 'model_stock')

Agents

Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3

Mixture of Experts Explained

Long context

Fine-tune Llama 3 with ORPO

Handbook v0.1 models and datasets