Convert large diffusion models into smaller, efficient versions for image generation without losing quality.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytime[ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.
q-diffusion has 377 stars on GitHub. It has been forked 27 times. q-diffusion is written mainly in Python. It has been in active development since 2023. q-diffusion is available under the MIT license. Its main topics are ddim, diffusion-models, model-compression, post-training-quantization.
[ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.
q-diffusion is an open-source project. It is released under the MIT license.
Yes. q-diffusion is free and open source — you can use, modify and self-host it.
q-diffusion is available under the MIT license.
q-diffusion is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/xiuyu-li-q-diffusion.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.