Diverse LLM Subsets via K-Means (100k-1m) [pretraining, If, Reasoning]
Posted3 months ago
github.comTechstory
calmpositive
Debate
0/100
LLMPretrainingAI Research
Key topics
LLM
Pretraining
AI Research
The post shares a GitHub repository implementing k-means clustering for creating diverse subsets of Large Language Models (LLMs) at a scale of 100K-1M, sparking interest in the methodology and potential applications.
Snapshot generated from the HN discussion
Discussion Activity
Light discussionFirst comment
N/A
Peak period
1
Start
Avg / period
1
Key moments
- 01Story posted
Oct 4, 2025 at 1:49 AM EDT
3 months ago
Step 01 - 02First comment
Oct 4, 2025 at 1:49 AM EDT
0s after posting
Step 02 - 03Peak activity
1 comments in Start
Hottest window of the conversation
Step 03 - 04Latest activity
Oct 4, 2025 at 1:49 AM EDT
3 months ago
Step 04
Generating AI Summary...
Analyzing up to 500 comments to identify key contributors and discussion patterns
ID: 45470824Type: storyLast synced: 11/17/2025, 11:03:29 AM
Want the full context?
Jump to the original sources
Read the primary article or dive into the live Hacker News thread when you're ready.
- Pre-Training: https://huggingface.co/datasets/AmanPriyanshu/stratified-kme... - Instruction-Following: https://huggingface.co/datasets/AmanPriyanshu/stratified-kme... - Reasoning: https://huggingface.co/datasets/AmanPriyanshu/stratified-kme...