3 ms·
Not really relevant bc it's kinda nitpicky but amazingly it's not even 4gb, it's more like 2gb if you use the float16 version (which has no quality degredations
by naillo 4y ago
Not really relevant bc it's kinda nitpicky but amazingly it's not even 4gb, it's more like 2gb if you use the float16 version (which has no quality degredations). Quite amazing that so many images fit in that small a package.
- latchkey 4y agoThat's how I felt about the original ipod.
- achr2 4y agoThe images do not. The output of the trained / weighted correlations do.
- naillo 4y agoExchanging compute for space in the space-compute tradeoff curve.
- mkaic 4y agohmm -- I tried converting to float16 just using a naive model.half() call and saw some quality degradation in my images compared to just autocasting parts of the model to float16 while leaving others at float32. Curious if anyone else has had the same experience.
- zone411 4y agoYou may want to try bfloat16 instead.
- naillo 4y agoMight be that there's some degredation but I think it's pretty close. Anyway I'm using their 'official' fp16 version which they might be doing some extra magic on idk. I.e. via StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16, ...)
- butwhywhyoh 4y agoBut you just said "no degradation".
- fomine3 4y agoCan I download ckpt file for fp16?