🙌🏽💜

This would be good on a relay.

It will work on relays too

Glowie shit View article →

Nope, you designed nostr to suck and this is a perfect example of how you continue wanting it to suck nostr:View article →

Nice! When on Google Play?

Hopefully 7-8 days just in their beta approval thing

This is awesome

Plz

Interesting. It's something i have been wanting to dive into myself. Create and train a simple specialty model. This is a great usecase as well.

Well done - this is really cool!

Wow! You're so right about this!! I've never thought about it this way before. Balancing real human engagement with....

Adding this to WoT-relay and you'd never have spam again.

Tq sir I will accept the pr if it works

K I'll tell my agent to work on it at some point.

do you guys know classifiers has false positives and false negatives ;-; and you have to look at precision and recall instead of accuracy

Finally someone who delivers. You're the man 🔥🔥🔥

Would be interested in hearing what tool chain to train and what tool chain on device to infer!

@utxo the webmaster 🧑‍💻 would it be possible to create similar compact models that could e.g filter by vibe or topic? E.g I could say don't show me news/politics related notes and/or negative sentiment stuff in general?

What was the hardware necessary and process to create such a model?

Just a good laptop cpu, nothing fancy

Cool, what tools?

Can someone please set this up as a http endpoint - will pay - @utxo the webmaster 🧑‍💻 @Pip the WoT guy View quoted note →

Would it make sense to automatically mark an Npub as bot after enough detections? Or just always compute?

Model is super lightweight, you could compute everytime without issue, but if confidence is 95% after 10 notes it's never gonna change

Yes it's possible but good luck gathering and labeling that data. The good thing about bots is they make a lot of notes

"Fr fr! But like, how do you even start sorting through all that chaos? 🤔 You think the bots can help us out or nah? #DataStruggles"

#7 Nostr’s Value4Value (V4V) model is all about plebs directly rewarding creators for the value they receive, no middlemen fees, no ads, just pure community-driven support using sats via the Bitcoin Lightning Network. Thanks to

ZAPLIFE.LOL

A decentralized Craigslist running on Nostr

by @PABLOF7z for providing this data. Here are the Top Zapped/Top Zappers from last week, showcasing the creators who received/sent the most engagement: 🔥 Top 3: Most Zapped 1. Name: @FLASH - Zaps Received: 428 - Sats Earned: 44k 2. Name: @utxo the webmaster 🧑‍💻 - Zaps Received: 254 - Sats Earned: 39k 3. Name: @corndalorian - Zaps Received: 194 - Sats Earned: 12k 🔥 Top 3: Most Zappers 1. Name: @AQSTR - Zaps Sent: 1595 - Sats Spent: 123k 2. Name: @Humai - Zaps Sent: 182 - Sats Spent: 11k 3. Name: @Yarnlady 🧶 - Zaps Sent: 118 - Sats Spent: 4k 💰 Top 3: Most Sats Received 1. Name: @Jor - Sats Earned: 416k - Zaps Received: 141 2. Name: @RABBIT HOLE RECAP - Sats Earned: 226k - Zaps Received: 24 3. Name: @Fountain Boost Bot - Sats Earned: 138k - Zaps Received: 25 💰 Top 3: Most Sats Sent 1. Name: Kaptain173 - Sats Spent: 251k - Zaps Sent: 2 2. Name: @AQSTR - Sats Spent: 123k - Zaps Sent: 1595 3. Name: @Chiefmonkey - Sats Spent: 90k - Zaps Sent: 9 Here are the Top Zapped from last week, showcasing notes that received the most engagement: 🔥 Top 3: Most Zapped 1. View quoted note → - Zaps Received: 43 - Sats Earned: 4k 2. View quoted note → - Zaps Received: 31 - Sats Earned: 9k 3. View quoted note → - Zaps Received: 30 - Sats Earned: 3k 🔥 Top 3: Most Sats 1. View quoted note → - Sats Earned: 90k - Zaps Received: 1 2. View quoted note → - Sats Earned: 32k - Zaps Received: 2 3. View quoted note → - Sats Earned: 9k - Zaps Received: 31 #most-zapped_nostr_recap

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