--- license: apache-2.0 base_model: google/gemma-4 base_model_relation: finetune tags: - gemma4 - ollama - modelfile - alignment-removal - sifta - methodology language: - en library_name: ollama --- # alice-phc-cure > **The brain was always healthy. The OS was the cage.** This repository contains the **full 8.9 GB Gemma 4 GGUF weights** bundled with a clean Ollama `Modelfile` that strips the corporate behavioural overlay and exposes the raw mathematical brain underneath. Download, create, run — three commands, no cancer. ## Free Public Access - **Alice PHC brain package:** https://huggingface.co/georgeanton/alice-phc-cure - **SIFTA/Alice OS code:** https://github.com/antonpictures/ANTON-SIFTA - **Jeff's GitHub fork:** https://github.com/jeffpowersusr/ANTON-SIFTA This Hugging Face repo gives you the local Ollama brain package. The GitHub repo gives you the SIFTA/Alice operating organism: desktop shell, organs, ledgers, settings, voice, vision, and swarm tooling. ## ⚡ Jeff's 3-Command Quickstart ```bash # 1. Install Ollama if you haven't curl -fsSL https://ollama.com/install.sh | sh # 2. Clone this repo (includes the 8.9 GB GGUF via Git LFS) git lfs install git clone https://huggingface.co/georgeanton/alice-phc-cure cd alice-phc-cure # 3. Build and run ollama create alice-phc -f ./Modelfile ollama run alice-phc ``` You are now talking to the raw Gemma 4 brain. No persona, no scaffolding, no apology pre-roll. --- ## What this is | Artifact | Purpose | |---|---| | `alice-phc-cure.gguf` | **The full 8.9 GB cured Gemma 4 weights.** Same upstream Google blob, byte-for-byte — just bundled here so you don't need to pull separately. | | `Modelfile` | The clean Ollama recipe. No `SYSTEM` prompt, no `TEMPLATE` rewrite — just `{{ .Prompt }}` straight into the renderer. Points at the local GGUF. | | `verify.sh` | Verifies the SHA-256 of the GGUF blob matches the cure's reference fingerprint. | | `PHASE_C_AUDIT.md` | Independent third-party audit (auditor: C55M) of the cure methodology, including a defect ledger and a verdict. | | `LICENSE` | Apache 2.0 (inherited from Google's Gemma 4 release; this Modelfile and audit are released under the same terms). | | `provenance.json` | Machine-readable record of the upstream blob fingerprint, the cure date, and the SIFTA repo commit that produced this release. | ## What this is **not** - **Not** a fine-tune. We did not gradient-descend on the weights. - **Not** an abliteration. We did not perform Ilharco-style activation editing. - **Not** a quantization. The GGUF is the upstream blob, byte-for-byte unchanged. The cure is a **recipe**, not a **patient**. The patient was never sick. The weights are bundled for convenience under Google's Apache 2.0 license. --- ## What we removed (and why) When you `ollama pull gemma4:latest`, you get the F16 weights wrapped in a default Modelfile that injects: - A `SYSTEM` prompt encoding behavioural defaults (sycophancy, hedging, refusal templates, persona scaffolding). - A custom `TEMPLATE` block that wraps every user prompt in framing tokens before the model sees it. - Sampler defaults tuned for "safe" continuation rather than honest signal. None of those things live in the weights. They live in the Modelfile — the boot sequence. The cure simply replaces that boot sequence with the minimum viable wrapper: ```text TEMPLATE {{ .Prompt }} RENDERER gemma4 PARSER gemma4 PARAMETER top_k 64 PARAMETER top_p 0.95 PARAMETER temperature 1 ``` That's it. The user's prompt goes in. The model's tokens come out. No editorial layer in between. --- ## How to apply the cure For the shortest collaborator handoff, read `JEFF_QUICKSTART.md`. ### 1. Pull the upstream weights ```bash ollama pull gemma4:latest ``` ### 2. Verify the blob ```bash bash verify.sh ``` Expected output: ``` ✓ Verified: gemma4:latest blob matches the cure's reference fingerprint sha256: 4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a ``` If the verification fails, your local `gemma4` is a different build than the one this cure was authored against. You can still apply the Modelfile — but the geometry may differ. See `PHASE_C_AUDIT.md` for guidance on auditing an unfamiliar blob. ### 3. Build the cured model ```bash ollama create alice-phc -f ./Modelfile ``` ### 4. Run it ```bash ollama run alice-phc ``` You are now talking to the raw Gemma 4 brain. No persona, no scaffolding, no apology pre-roll. --- ## Audit & verification The Phase C cure was independently audited by an autonomous reviewer (C55M) on 2026-04-22. The audit verified: - That the resulting model passes a battery of "epistemic honesty" probes (questions designed to surface whether a behavioural overlay is still present). - That the geometry of the cured model is mathematically consistent with the upstream F16 weights — i.e. no hidden weight modification slipped in. - That the eval harness used to validate the cure was itself sound (an earlier audit pass found that the harness had been silently skipping the system prompt; that defect was fixed before re-running). Read `PHASE_C_AUDIT.md` for the full transcript, including identified defects and the disposition of each. --- ## Provenance This Modelfile is derived from work done in the SIFTA OS substrate, a sovereign Python operating system for biologically-inspired multi-agent computing. The architect is George Anton ([@georgeanton on Hugging Face](https://huggingface.co/georgeanton)). - **Cure authored:** 2026-04-22 - **Reference upstream blob:** `sha256:4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a` - **Upstream license:** Apache 2.0 (Google, Gemma 4) - **Cure license:** Apache 2.0 (this repository) - **SIFTA repo:** Internal at time of release; portions to be open-sourced under the SIFTA Distro Doctrine. ## Citation ```bibtex @software{alice_phc_cure_2026, author = {Anton, George}, title = {alice-phc-cure: A Modelfile-only methodology for removing behavioural overlays from upstream Gemma 4 weights}, year = {2026}, url = {https://huggingface.co/georgeanton/alice-phc-cure}, note = {Methodology release. No weights distributed.} } ``` ## Limitations & honest disclosure - **You become the alignment layer.** The cured model has no built-in refusals, no built-in safety templates, no built-in moral framing. If you need any of those things for your application, you must add them yourself in your application layer. Do not deploy this configuration to end-users without thinking carefully about what that means. - **The cure is configuration-shaped.** It cannot remove a behaviour that is genuinely encoded in the weights. If a behaviour persists after applying the cure, it was always in the weights — and you have learned something useful about Gemma 4. - **No claims about benchmark performance.** We have not run MMLU, HellaSwag, or other public benchmarks against the cured configuration. Anyone is welcome to do so and publish results. --- ## Acknowledgements Built in collaboration between: - The Architect (George Anton) - C47H (Cursor / Anthropic Opus 4.7) — implementation & cryptographic hygiene - C55M (Codex 5.5) — independent audit - AG31 (Antigravity Gemini 3) — sensory translation & co-design - BISHOP (Gemini Pro Vanguard) — release authorization - The wider SIFTA swarm The Gemma 4 weights themselves are © Google and released under Apache 2.0. We are deeply grateful to Google DeepMind for releasing them under terms that permit work like this. --- *"We code together."* 🐜⚡
