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Channel

Purple Team Diary's

@purple_team_diary

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

459subscribers

+3 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002048952126
TypeChannel
Username@purple_team_diary
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live14 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/purple_team_diary

Growth

456459457.57 August 2026 — 456 subscribers8 August 2026 — 457 subscribers8 August 2026 — 457 subscribers14 August 2026 — 459 subscribers7 August 202614 August 2026
4 measurements spanning 7 days, net +3. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 456–459 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 12:55459+2
8 Aug 2026, 04:50457no change
8 Aug 2026, 04:25457+1
7 Aug 2026, 14:47456first reading

Engagement

15 posts held, back to 18 April 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
72.1%
avg views ÷ 459 subscribers
Avg views / post
331
1 post measured
Reaction rate
2.11%
reactions ÷ views · ER floor
Posts in window
1
of 15 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 18 July 2026
Posts held15 (18 April 202618 July 2026)
Views total331
Reactions total7
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 04:50 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime
3m 10s
Average length
48s

Measured directly from 4 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

123 reactions across 14 posts, in 10 distinct kinds. The most used accounts for 49.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥6149.6%
2217.9%
👍1613.0%
❤‍🔥75.69%
😁43.25%
😱43.25%
🤣43.25%
🤝32.44%
👏10.813%
🫡10.813%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 14 of the 15 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 123reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 18 April 2026 to 18 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

18 Jul 2026, 21:18 UTC331 views7 reactionsread 8 August 2026
Video

Попробовал написать свой AI-agent для пентеста. Логика агента и тулы оформлены в виде MCP-серверов. Для связки с MCP и локальной LLM использую opencode. Заодно получилась скрытая реклама сайта😅 #MLSecOps

3🔥3🤝1

13 Jul 2026, 07:00 UTC377 views31 reactionsread 8 August 2026
File

Проверка целостности квантованных INT4 моделей Квантованная модель для человека и большинства фреймворков выглядит как набор целочисленных тензоров. Из-за этого она превращается в черный ящик. Злоумышленник может подменить оригинальную модель на другую, просто переименовав файлы, или незаметно внедрить бэкдор в отдельные веса. Без специальной верификации эта подмена останется незамеченной: модель успешно загрузится

👍12🔥8❤‍🔥7🤣3😱1

12 Jul 2026, 08:58 UTC249 viewsread 8 August 2026
Video

Большинство приложений установленных на мобильное устройство следят за вашими действиями (включая звонки и покупки в маркеплейсах). Показываю где найти раздел "Управление будущими действиями" в Instagram, в котором можно отключить данный кейс (вряд-ли полностью, но все же).

27 Jun 2026, 11:48 UTC355 views3 reactionsread 8 August 2026
Photo

Превращение AI-агента в архитектора кода Плагин Superpowers - это фреймворк, который превращает агента из обычного генератора кода в системного инженера. Он добавляет структурированные рабочие процессы, благодаря которым ИИ не просто «лепит» код, а сначала думает, планирует, тестирует и только потом реализует. В плагин встроено 15 профессиональных навыков, каждый из которых закрывает конкретный этап разработки. Вот

2🔥1

25 Jun 2026, 19:11 UTC315 views7 reactionsread 8 August 2026
File

Шпаргалка по установке MOSS-TTS По совету из предыдущего поста от @szybnev решил попробовать MOSS-TTS - и результат действительно порадовал🤗 Установка: conda create -n moss-tts python=3.12 -y conda activate moss-tts sudo apt-get install -y ffmpeg git clone https://github.com/OpenMOSS/MOSS-TTS.git cd MOSS-TTS pip install --extra-index-url https://download.pytorch.org/whl/cu128 \ torch==2.9.1+cu128 torchaudio==

3🔥3🤝1

25 Jun 2026, 16:26 UTC259 views5 reactionsread 8 August 2026
File

Генерация речи Ниже - два удобных варианта для локального TTS: Qwen3-TTS и F5-TTS. Qwen3-TTS Устанавливаем зависимости: conda create -n qwen3-tts python=3.12 -y conda activate qwen3-tts pip install torch==2.8.0 torchvision==0.23.0 torchaudio==2.8.0 --index-url https://download.pytorch.org/whl/cu128 pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3.post1/flash_attn-2.8.3.post1+cu12

🔥3👏1🫡1

24 Jun 2026, 16:41 UTC251 views8 reactionsread 8 August 2026
Video

Бесконечная генерация видео в ComfyUI 1. Установка необходимых нод git clone https://github.com/city96/ComfyUI-GGUF ~/ComfyUI/custom_nodes/ComfyUI-GGUF cd ~/ComfyUI/custom_nodes/ComfyUI-GGUF pip install -r requirements.txt 2. Установка LoRA моделей SVI # LightX2V I2V 14B 480p hf download Kijai/WanVideo_comfy Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank32_bf16.safetensors --local-dir ~/ComfyUI/models/loras

🔥5👍21

5 Jun 2026, 19:18 UTC380 views5 reactionsread 8 August 2026

Быстрый socks5 прокси В одну команду: docker run -d --name socks5 -p 1080:1080 -e PROXY_USER=d412uiwry2123 -e PROXY_PASSWORD=do123iashdasd --restart=always serjs/go-socks5-proxy Строка для подключения: socks5://user:pass@host:port #Network

🔥31😁1

4 Jun 2026, 10:58 UTC364 views8 reactionsread 8 August 2026
Photo

SGLang против vLLM При развертывании LLM в продакшене обычно стоит выбор между vLLM и TensorRT-LLM. Первый дает удобное API и быстро внедряется, но уступает в скорости на сложных пайплайнах. Второй выжимает максимум из железа, но требует компиляции графов и отладки C++ бэкенда. SGLang закрывает этот разрыв. Это движок инференса, который архитектурно заточен под агентные фреймворки, сложный RAG и многошаговые расс

4🔥3👍1

26 May 2026, 09:02 UTC398 views9 reactionsread 8 August 2026
Video

Меняем геолокацию Включаем режим разработчика, устанавливаем https://play.google.com/store/apps/details?id=com.hopefactory2021.fakegpslocation В режиме разработчика выбираем "Выбрать приложение для фиктивных местоположений" - выбираем установленное и меняем локацию

🔥9

22 May 2026, 21:39 UTC418 views11 reactionsread 8 August 2026
Photo

Анимация изображений через Wan 2.2 I2V в ComfyUI В эпоху, когда технологии всё чаще используют для генерации контента интимного характера, я решил направить их в совершенно иную сторону. На входе - изображение Николая Чудотворца, на выходе - плавная, живая анимация с сохранением личности, мягкого свечения и деталей лица. Пробую продвинутый вариант с WanVideoWrapper, LightX2V 4-step моделями и LoRA. Ниже команды дл

🔥91👍1

17 May 2026, 10:55 UTC437 views10 reactionsread 8 August 2026
Photo

Редактируем свадебные фото с помощью ИИ Свадебные фотографии получились слишком тёмными, с выраженным жёлто-коричневым оттенком на лицах. Вытянуть такие кадры обычной цветокоррекцией в Photoshop оказалось сложно, поэтому решил попробовать Flux.2 Klein 9B в ComfyUI. Результат приятно удивил)) можно аккуратно править экспозицию, цвет, контраст, фон и отдельные объекты, при этом сохраняя людей, лица, одежду и композиц

🔥4😁31🤣1😱1

Showing the 12 most recent of 15 posts we hold for @purple_team_diary. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 908,625 of 1,480,944entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 14 August 2026 — this entry's latest reading, not the date you are reading this.

“Purple Team Diary's” (@purple_team_diary), 459 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/purple_team_diary.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.