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NVlabs / Sana

SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
https://nvlabs.github.io/Sana
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Info about other tokenizer #26

Open chri002 opened 7 hours ago

chri002 commented 7 hours ago

Amazing work. An info about the tokenizer, in the tokenizer and embedded code there are references about Qwen2-0.5B-Instruct and 1.5B; I wanted to know if there have been any tests using them and if so, what precision and fidelity they achieved. Because using them could greatly reduce the VRAM.

An other info, Is there any chance that an inference with offloading of the various models is planned, for low end PCs?

lawrence-cj commented 5 hours ago

Qwen is not tested in Sana. And what do you mean by offloading for low end PCs?

chri002 commented 5 hours ago

Thanks for the info on qwen, regarding offloading I mean loading and unloading the various parts or layers into RAM so as to fit Sana into a 8 or 6 gb GPU (and maybe even 4gb) besides running for example vae on CPU or even part of gemma. After all gemma also runs on 6gb desktop GPU and android with 8gb RAM.