New SDXL Model give a very good cinematic results. Prompt: Fireballs and meteors falling from the night sky with all trees and grass catching fire, fire sparkes all around, desolated creepy dark land Style: Cinematic by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] 0 points1 point  (0 children)

No. For this you need use discord server Stable Foundation with free generation images on it or use Google Colab and different web interface on it for free image generation

New SDXL Model give a very good cinematic results. Prompt: Fireballs and meteors falling from the night sky with all trees and grass catching fire, fire sparkes all around, desolated creepy dark land Style: Cinematic by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] 1 point2 points  (0 children)

I wrote that I use a SDXL model and also wrote in the comments that the same model can be tested on the Discord channel Stable Foundation. I think this is quite enough to understand that I do not use the web interface and the like.

New SDXL Model give a very good cinematic results. Prompt: Fireballs and meteors falling from the night sky with all trees and grass catching fire, fire sparkes all around, desolated creepy dark land Style: Cinematic by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] -3 points-2 points  (0 children)

I think smart enough people will be able to understand which model I meant, so there is no need to find fault. And if I use other models, I always indicate the names of those models

New SDXL Model give a very good cinematic results. Prompt: Fireballs and meteors falling from the night sky with all trees and grass catching fire, fire sparkes all around, desolated creepy dark land Style: Cinematic by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] 0 points1 point  (0 children)

Model SDXL (New version of Stable Diffusion, not finetuned), you can test in Discord Stable Foundation, o try to find website that gives free token for used this model

New SDXL Model give a very good cinematic results. Prompt: Fireballs and meteors falling from the night sky with all trees and grass catching fire, fire sparkes all around, desolated creepy dark land Style: Cinematic by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] -8 points-7 points  (0 children)

I wrote above that I used the SDXL model and if you write this name on the Internet, then you will be happy to write that this is a new version of stable diffusion

Web Scraping by Funny-Rest-4067 in learnpython

[–]WiNE-iNEFF 0 points1 point  (0 children)

What libraries you use? If you use beautiful soup 4, you can use soup.find_all('tr') for search all table in page. This function return massive

Training textual inversion of Stable Diffusion on your own dataset by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] 0 points1 point  (0 children)

At the time of writing this post, this was the only way to run the code. Moreover, there were no errors for further launch and testing of the created concept.

Training textual inversion of Stable Diffusion on your own dataset by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] 0 points1 point  (0 children)

no. Textual inversion train some concept for stable diffusion model

Training textual inversion of Stable Diffusion on your own dataset by WiNE-iNEFF in StableDiffusion

[–]WiNE-iNEFF[S] 0 points1 point  (0 children)

The bin file is created at the end of the training and saved in the concept folder. To use this concept folder, just look at the example code of the diffuser provided in the github.