//=time() ?>
YouTube Speedpaint -> https://t.co/Nrltu1xGJL
I had a raffle going on my Discord and this was the winners final piece, their Acrocantho! B)
Sticking to my 2023 goal of training painting more again :3
My Discord server -> https://t.co/aKEd76q9Wg
#acrocanthosaurus #paleoart
some of the decals under training mode directories, these were meant to be used in a plethora of early training maps
Training sketches to know to draw the Omnic “Moses” and... I had fun giving it more human expressions (the ironyyyyyyyyyyyyyyyyyyyy !🤣)
#Overwatch2 #ow2 #fanart #sketch #artistontwitter #TheHusbanbot #Ramattra
Cernunnos (Original)
Art made on Photoshop CS5 during 2 days like training.
#Art #DigitalArt #PhotoshopCS5 #Original #Mythology #Celtic #Cernunnos #Nature #Green #CelticMythology #Girl #ArtTraining #Beauty #Brushing #Cartoon
@Frosty_Arts_ Intro: I’ve never seen a form like that it looks strong I better go all out!
Victory: wow….. you were strong….. guess I still have some more training to do I hope we can fight again some day
@KonoharuBun Intro: You’re different from other people I’ve seen let’s see what you’ve got!
Victory: that was super fun! Thanks for the training!
@Sayo_Nyara hi! I'm bella pawesborne and im a shiba inu vtuber! I love drawing, singing, and playing video games. I actually have had formal training in classical voice, so I rlly like opera and singing operatically!
@AyemYou1 Pick up the soldiers and start training! see you at camp! #MXBEARS
https://t.co/ZK33jIXCzu
@NftUrbandragons @cocky_juice @alba_luxia
@JoeBangles11 Good Morning, have a lovely day. How’s the training going ?
Goku went from, "There's a point where extra training is just torturing your body," to, "Lets train for 3 years in the room for the heck of it." Lol.
@RavenRelic121 Intro: Not only do you got a gnarly style but you seem pretty strong. Try your best to satisfy me
Win: That was certainly entertaining, make sure to come back to me anytime you’d like I could always use a training partner 😏
@noop_noob test5 has slightly more training images than 1.3.0, and the output is close to 1.3.0, but degraded.
In 1.3.0, I did a 512x512 cropping step, but in test5 I did not do that, but used aspect ratio bucketing.
Maybe the same procedure with the exact same dataset would reproduce 1.3.0
@noop_noob Yes...
I am currently testing a WD1.4 based model that dataset with different contents to verify why v1.3.0's outputs are so nicely.
Even if I increase the number of training images, I cannot exceed the miraculously created 1.3.0. I cannot reproduce it... 😭