Vadim Kulibaba

Sorry, right now you may include only as library project. You may see how in example here: https://github.com/recoilme/android-DisplayingBitmaps

Oh( I am not sure, may be add some checks on recycled, before rendering? pseudocode: ``` if (bitmap != null && !bitmap.isRecycled()) do some with bitmap ```

Заводим в телеграм бота. Кладем в корень файл telefeed.bot c токеном нашего бота И все получится

Hi, thanks for response! Ok, at first of all we need good samples for test. For nice pictures we need: - two good different type models ([photorealistic](https://civitai.com/api/download/models/37432), [illustration](https://civitai.com/api/download/models/44827)) - right...

Prompts examples. Minimal negative prompt is: (low quality:1.4), (worst quality:1.4) Positive prompts must contains something like this: `highres, masterpiece, perfect lighting, bloom, cinematic lighting, ,(masterpiece:1.3), (best_quality:1.3), (ultra_detailed:1.3), 8k, extremely_clear, realism,...

Samplers Example of patched sampler: https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8457 Github with samplers: https://github.com/crowsonkb/k-diffusion (Katherine Crowson, [@crowsonkb](https://github.com/crowsonkb) - developer of most famous diffusion samplers, including DPM++ SDE Karras) May be she may get some...

And last, about "Another idea is to not apply the same amount of merging to every layer. For instance, there are 4 layers ToMe is applied to right now. What...

For me this script working on m1 ``` import torch, tomesd from diffusers import StableDiffusionPipeline model_id = "./colorful_v30.ckpt" pipe = StableDiffusionPipeline.from_ckpt(model_id, torch_dtype=torch.float32).to("cpu") # Apply ToMe with a 50% merging ratio...

So, i have 2 news) Good and Bad. How run on mac m1: - replace in merge.py int64 on int32 - add in random init type int32 - get error...

"Patched with 0.5/0.3"