How fast samyak112/pym-particles is gaining stars, and where it lands on Trendshift and GitHub Trending
Activity and trending
Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending
Jun 2026 – Oct 2026
Stars +74in 5 months
0204060
53
Forks +5in 5 months
0246
5
Merged PRs 3in 5 months
0123
3
Trendshift Trendingthe best rank each month, on any day it made the top 25
Not in the Trendshift top 25 in this period
Jun 2026Jul 2026Aug 2026Sep 2026Oct 2026
The left and right arrow keys step from month to month; Home and End go to the first and the last
Stars, forks, merged pull requests and best Trendshift Trending rank, by month
Month
Stars gained
Forks gained
Merged PRs
June 2026
+53
+5
3
July 2026
+19
+0
0
August 2026
+2
+0
0
September 2026
+0
+0
0
October 2026
+0
+0
0
Total
+74
+5
3
1#1 on the list
7Best rank that month
Not trending
Social mentions
Recent discussions about this repository across the web
1 post
I have been trying to tweak ai to make it think different things 1. Used a 900kb transformer to overfit a single file so that it can be used as a compressor 2. Tweaked the transformer architecture a…
I overfitted a 900KB LLM to compress a 100MB file into 7MB. You know how you can paste a paragraph into ChatGPT and ask it to repeat it back exactly? Just that on steroids. ZIP: 27MB My model: 7MB…
Context compression for AI coding agents: compresses tool output before it enters the model, dedups repeats to 13-token refs. Claude Code, Cursor, Codex, Kiro, Zed, any MCP client. Rust, zero LLM calls.
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
