Spaces:
Running
Deploying this directory as a HuggingFace Space
This directory is a self-contained static HuggingFace Space ready to push. Total bundle size is ~124 MB (the bulk is the two 60K data packs at 61 MB each); the index.html + scripts + weights together are under 3 MB.
One-time setup
You need: a HuggingFace account, the huggingface_hub Python CLI, and an HF write token.
pip install -U huggingface_hub
huggingface-cli login # paste your token from https://huggingface.co/settings/tokens
Install Git LFS once (required for the 60 MB data packs):
brew install git-lfs # macOS; apt-get install git-lfs on Linux
git lfs install
Create the space and push
# 1. Create an empty static space named cortex-conv on huggingface.co/spaces/<your-username>/cortex-conv
huggingface-cli repo create cortex-conv --type space --space-sdk static
# 2. Clone the empty space repo somewhere
git clone https://huggingface.co/spaces/<your-username>/cortex-conv ~/cortex-conv-space
# 3. Mirror this directory into the clone
rsync -a --delete --exclude=.git /Users/exobit/developer/fnm-gpu/hf_space/ ~/cortex-conv-space/
# 4. Push (the .gitattributes file already routes the JSON packs to LFS)
cd ~/cortex-conv-space
git lfs track "*.json"
git add .gitattributes README.md index.html PAPER_COMPANION.md tests/ weights/ mnist/ fashion/
git commit -m "initial: cortex-conv ships pre-trained at 96.8% MNIST"
git push
The Space will build automatically (a static space is just a file server, no build step). Open https://huggingface.co/spaces/<your-username>/cortex-conv and the page should load at 96.8% MNIST test accuracy within ~3 seconds on first visit.
Verifying the deployed space
Visit the Space URL with a Chrome/Edge/Safari browser that supports WebGPU. Within 3 seconds you should see:
- Test accuracy: 96.8%
- Status label:
idle (cortex-conv · webgpu+pretrained · 34,106 params) - Equation header:
CORTEX-CONV (2-conv 16,16, γ=0.1, banked V1 mask, drive-clamp · 34,106 params) · CORTEX NEURON · ADAGO · MNIST
If WebGPU is unavailable in the visitor's browser, the page falls back to a CPU-only path with the embedded 6K MNIST and runs much slower.
Notes
- HuggingFace Spaces by default serve from CDN with proper MIME types for
.jsonand.js— no extra config needed. - The
sdk: staticline inREADME.mdfrontmatter is what tells HF this is a static site (not a Gradio or Streamlit app). - Updates: after editing files in
/Users/exobit/developer/fnm-gpu/hf_space/, repeat thersync+git add+git commit+git pushsteps. HuggingFace re-deploys automatically on every push. - To regenerate the bundled weights snapshot after architecture changes, run
tools/train_cortex_dump.cjsfrom the project root (not fromhf_space/), then copy the resultingweights/cortex_conv_mnist_R28.jsonintohf_space/weights/.