The magic happens in 'C:\Program Files\LGHUB\data\applications.json'
The important thing to note is the per-entry "detection" object, which is a list of detection methods, e.g.
Key:
- c = character
 - d = digit
 - "/ppp/ppp" = path
 - {uuu} = UUID
 
| Waltz, Bad Nymph, For Quick Jigs Vex. ce, gq, mn, yz, DO, TI, 0O, 1iIlL, 2Z, 4A, 5S, 7TZ, 8B, @ | 
The magic happens in 'C:\Program Files\LGHUB\data\applications.json'
The important thing to note is the per-entry "detection" object, which is a list of detection methods, e.g.
Key:
e.g. Amazon, EBay, etc.
If you’ve observed 8 ravens and they’ve all been black, how certain should you be the next raven you see will also be black?
According to the Rule of Succession, 90%.
In general, the probability is
These are companies/owners/CEOs/major shareholders which
(FYI, many companies "cover thier bets" by donating equally to both parties)
Source https://youtu.be/vz6lHO4ezy8
| # Output the current moon phase as an emoji for your prompt. | |
| import juliandate as jd | |
| from datetime import datetime | |
| def calc_phase(year: int, month: int, day: int) -> int: | |
| fixed_date = 694039.09 # NON-JULIAN days since 1900-01-01 🤷 | |
| days_per_cal_month = 30.436875 | |
| Julian_Y2K = 2451544.5 # Julian 2000-01-01T1200 | 
| [ADDON] | |
| [email protected] | |
| [DEPTH] | |
| DepthCopyBeforeClears=0 | |
| UseAspectRatioHeuristics=0 | |
| [GENERAL] | |
| EffectFrameDelay=500 | |
| EffectSearchPaths=C:\Guild Wars 2\addons\reshade\gshade-shaders\Shaders,C:\Guild Wars 2\addons\reshade\gshade-shaders\ComputeShaders | 
Make Windows accept File Paths over 260 characters Enable Win32 Long Paths through Regedit
To enable Win32 long paths through Regedit-
Open Regedit
Paste the path for the file system folder
Find the LongPathsEnabled DWORD file and double click on it
Change to value from 0 to 1 and click OK
| From somewhere in the bowels of https://www.reddit.com/r/StableDiffusion/comments/y0t4pd/a_bizarre_experiment_with_negative_prompts/iru7rh8 | |
| by Ok_Entreprenuer_5833 | |
| If anyone is wondering why this effect happens (and they should be wondering if they want to push SD to it's limits) it's the SEO media marketing word cloud noise coming up in the labelling of the dataset SD was trained on. | |
| I'll try not to be long winded, want to get back to my SD project but think it's valuable enough to put down here since this experiment is a clear visual aid for the idea. | |
| Top searches in 2019 in my example here: (didn't use 2020 onward as results of covid would skew this out of normalization). | |
| News, people, celebrities and Trump is up there among all those at the top. | |
| Disney |