sIlENtbuffER / Generative-Models
Generative models from scratch, progressively implemented in NumPy, C, and CUDA to uncover what ML frameworks hide.
Why this job: topics: stable-diffusion, diffusion-models
What it does
A learning project that works through generative models from first principles, no ML frameworks involved. Each model on the roadmap gets implemented up to three times, in increasing order of how much a framework normally hides from you:
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 34 days ago
- Stars
- 159
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- C
- 48% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- None
- No issues filed
- Pull requests
- 5 merged
- 0 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- C 48%
- Cuda 39%
- Python 12%
- CMake 1%
Topics
- cuda
- diffusion-models
- flow-matching
- gan
- generative-models
- numpy
- stable-diffusion
- vae
Project record
- JobImage generation
- StatusListed
- Commits6
- Forks16
- Watching16
- Stars in 28 days+51
- CreatedAug 19, 2026
- First seen by usNov 7, 2026
- CheckedNov 7, 2026