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license: apache-2.0

Staff Protocol — OICIO Internal Operations

Credits: deepRcurs Labs, @deeprcurs
Author: Mzed Imamkh, @mzedimamkh
Version: 0.6.0 — MatMul-Free CPU-Only
Account: deeprcurs-staff

GitHub: https://github.com/deepRcurs/OICIO
HuggingFace Hub: https://huggingface.co/deepRcurs/OICIO

This document contains internal operational rules for snapshot management, swap handling, and free-tier infrastructure automation. It is separated from the public README to keep the public documentation professional, academic, and focused on architecture.

Implementation — Snapshot Rules

Snapshot limit: 128MB / 10K files

Snapshot-safe (<1MB): Code only oicio/ Python POC + oicio-rs/ Rust CPU-only + whitepapers + README + Dockerfile + app.py + .github/workflows

Excluded (can re-download, outside snapshot):

  • .cache/: Rust toolchain (Cargo, rustup), Python venv (torch 191MB CPU, transformers, safetensors, fastapi, gradio), models (BitNet 2B 1.1GB), swap files (10GB+5GB=14GB active, autoscale 20GB,30GB), checkpoints (32MB)
  • .venv/: Python venv
  • .cargo/, target/, oicio-rs/target/: Rust build artifacts
  • __pycache__/, *.pt, *.safetensors: Cache and weights
  • Total excluded: ~17GB

Rules:

  • Do not disturb snapshot: keep code <128MB / 10K files, toolchain in .cache excluded
  • If RAM insufficient by calculation, swap before OOM: OS swap 10GB,20GB,30GB... in .cache + Python/Rust offload via memmap2

Proof:

  • Snapshot: 64 files, 526KB total after cleanup, 57 files 466KB after Rust port
  • Swap: 14GB active (10+5), autoscale logic to 20GB demonstrated
  • Training: 6.8M model 50 steps 23.4s loss drop 0.0111 sparsity 31->34% in 1.9GB RAM + 14GB swap
  • Real weights: BitNet 2B 1.1GB safetensors 542 tensors loaded, ternary matmul no mul
  • Rust binary: 501KB native + 607KB musl static (like Needle2 14MB) + 4.5MB generated via rustc CPU-only, all MatMul-free CPU-only

Infrastructure — Free Tier Without Credit Card/Phone

For automation without manual steps, using 2 tokens (GH + HF) shared:

  • GitHub Token ghp_... (repo scope): Push to deepRcurs/OICIO, setup Actions Secrets, trigger training in GitHub Actions Free (2-core CPU, 7GB RAM, 2000 min/month, no credit card, no phone verification). Already proven: Run 32607984794 status completed success with 11 steps success including Rust build 501KB and training from scratch HERE and push checkpoint to HF Hub via secret.

  • HF Token hf_... (write): Push to HuggingFace Hub deepRcurs/OICIO (100GB private free, 5TB public best-effort, no credit card, no phone). Already proven: 68 files including BitNet 2B 1.1GB real weights + training logs pushed from GitHub Actions.

  • MyBinder.org: No account needed, just GitHub repo public https://github.com/deepRcurs/OICIO, VM 2GB RAM, auto-build https://mybinder.org/v2/gh/deepRcurs/OICIO/main, no credit card, no phone.

  • Cloudflare R2: 10GB free forever, 1M write, 10M read, unlimited egress, no credit card required per tutorial, S3-compatible, for backup.

  • GitHub Releases: Unlimited for public repo, for 14MB binary and whitepapers.

HF Spaces Free CPU per 2026: As of July 2026, free CPU Basic for Gradio/Docker Spaces discontinued for new free users (community complaint 12 July 2026: "completely eliminate the free CPU Basic instance flavor"), only ZeroGPU remains with quota 3.5 min/day and Static Spaces free. So training in HF Spaces free is not feasible, but GitHub Actions free still works and Hub storage still free.

Final URLs:

Swap Management:

  • OS-level swap files in .cache (excluded): 10GB, 20GB, 30GB... autoscale if RAM >80%
  • Python-level offload via memmap2: offload KV cache, gradients, optimizer states to disk before OOM
  • Rust-level: memmap2 for tensor offloading

Training Automation:

  • GitHub Actions workflow .github/workflows/train.yml triggers on push to main
  • Steps: setup swap 10GB+5GB=14GB, build Rust 501KB, training from scratch HERE 6.8M 50 steps, push checkpoint to HF Hub via HF_TOKEN secret
  • Proven SUCCESS Run 32607984794 with 11 steps success

Storage:

  • HF Hub: 100GB private free, 5TB public best-effort, no credit card, no phone, just email
  • R2: 10GB free forever, no credit card per tutorial
  • GitHub Releases: unlimited for public repo

This file is internal staff protocol, separated from public README to keep public docs professional and academic.

Credits: deepRcurs Labs @deeprcurs / Mzed Imamkh @mzedimamkh