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Implementation of Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models

active 2023-08-152025-04-11 (UTC)

Complete coverage26,514 / 26,514 hourly files (100%) · 2 absent upstream2023-08-152026-08-23 (UTC)
Events
96
Pushes
0
Pull requests
0
Issues
4
Stars
84
Forks
3

Activity over time

Daily event counts in the loaded window

Line chart, 606 days from 2023-08-15 to 2025-04-11. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 4 total, peak 1 in a day. Comments: 5 total, peak 3 in a day. Stars: 84 total, peak 4 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
h3clikejava3003
zhanjiahui2001
bsun08021000
wangyePHD1001
yudongjian1000
alimohammadiamirhossein1000

Recent activity

Latest issues, pull requests and releases

  • Issue#31yudongjian2024-01-17 05:49
    images and resources for pre-training
  • Issue comment#24h3clikejava2023-11-14 02:58
    BUG in inference.py
  • Issue comment#28h3clikejava2023-11-14 02:57
    Problem with running the code both in colab and local machine
  • Issue comment#18h3clikejava2023-11-14 02:53
    I fine-tuned the same yannlecun image as yours, and the generated results are different from yours. I used the pre-trained model e4t-diffusion-ffhq-celebahq-v1 you released. Why are the results different?
  • Issue comment#25zhanjiahui2023-10-31 12:22
    Need help... OOM with 2 RTX3090 (bs=2)
  • Issue#30zhanjiahui2023-10-30 07:27
    Question about settings and results.
  • Issue comment#29wangyePHD2023-10-24 14:36
    {placeholder_token} vs *s in inference
  • Issue#29bsun08022023-10-20 00:56
    {placeholder_token} vs *s in inference
  • Issue#28alimohammadiamirhossein2023-09-23 04:46
    Problem with running the code both in colab and local machine

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 84 stars here means stars gained during the window, not the repo's star count.