Text Generation
Transformers
PyTorch
English
burt-imma
custom-architecture
matrix-memory
equilibrium-propagation
cifg
sovereign
snapkitty
no-backprop
formal-verification
lean4
agents
python
Instructions to use Snapkitty/burt-imma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Snapkitty/burt-imma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Snapkitty/burt-imma")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Snapkitty/burt-imma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Snapkitty/burt-imma with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Snapkitty/burt-imma" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Snapkitty/burt-imma", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Snapkitty/burt-imma
- SGLang
How to use Snapkitty/burt-imma with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Snapkitty/burt-imma" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Snapkitty/burt-imma", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Snapkitty/burt-imma" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Snapkitty/burt-imma", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Snapkitty/burt-imma with Docker Model Runner:
docker model run hf.co/Snapkitty/burt-imma
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Download README.md from Snapkitty/burt-imma: direct link, hf CLI and curl.
- Browser
- Download file 3.6 kB
-
https://huggingface.co/Snapkitty/burt-imma/resolve/main/README.md
- Command line
-
hf download hf://Snapkitty/burt-imma/README.md
-
curl -L -o README.md https://huggingface.co/Snapkitty/burt-imma/resolve/main/README.md
3.6 kB
| license: other | |
| license_name: snapkitty-tri-license | |
| license_link: https://huggingface.co/Snapkitty/burt-imma/blob/main/LICENSE.tri | |
| language: | |
| - en | |
| tags: | |
| - pytorch | |
| - custom-architecture | |
| - matrix-memory | |
| - equilibrium-propagation | |
| - cifg | |
| - sovereign | |
| - snapkitty | |
| - no-backprop | |
| - formal-verification | |
| - lean4 | |
| - agents | |
| - python | |
| library_name: transformers | |
| pipeline_tag: text-generation | |
| model_type: burt-imma | |
| datasets: | |
| - SNAPKITTYWEST/sovereign-training-corpus | |
| metrics: | |
| - perplexity | |
| widget: | |
| - text: The architecture of learning is | |
| example_title: Generation sample | |
| > Source: [github.com/SNAPKITTYWEST/burt-imma](https://github.com/SNAPKITTYWEST/burt-imma) | |
| # BURT-IMMA | |
| **Matrix-Memory Equilibrium Propagation - a 13-layer architecture that forks the backprop lineage.** | |
| SnapKitty West / SNAPKITTYWEST - Evidence or Silence - 2026 | |
| --- | |
| ## Model Description | |
| 13-layer architecture. Learning rule is Matrix-Memory Equilibrium Propagation (MMEP): two-phase, locally computable, Hebbian-style update. No gradient tape. No weight transport. | |
| Core memory cell (CIFG): | |
| ``` | |
| C_t = f_t * C_{t-1} + (1-f_t) * (v_t outer k_t) | |
| ``` | |
| | Component | Description | | |
| |---|---| | |
| | CIFG Matrix Memory | Full d x d state, sum-inversion retrieval | | |
| | MMEP Learning Rule | Two-phase local update, no backprop | | |
| | Entropy-Constrained Router | H(alpha) <= 0.20 nats (sovereign_entropy.tex) | | |
| | Spectral Projection | Contractive relaxation guarantee | | |
| | SmoothLeaky Activation | 4-axiom formal specification | | |
| | Boolean Perceptron Actors | Huntington postulate-verified routing | | |
| | 7 CUDA Kernels | sm_86 (RTX 3080) | | |
| | Lean 4 Formalization | Machine-checked proof ledger | | |
| --- | |
| ## Training | |
| - Hardware: RTX 3080 sm_86, 7 custom CUDA kernels | |
| - Learning rule: MMEP (no Adam, no SGD) | |
| - Corpus: SNAPKITTYWEST/sovereign-training-corpus | |
| - Weights: Architecture + code released; pretrained weights pending | |
| --- | |
| ## Papers - 11 Total (8 Zenodo + 3 In-Repo LaTeX) | |
| | File | Lines | Venue | Title | | |
| |---|---|---|---| | |
| | gdr_kernels.tex | 460 | SC / MLSys | **GDR-9: Formally Verified Generalized Delta Rule Kernel Stack Across Nine ISAs** | | |
| | liquidops_kernel.tex | 566 | PLDI / ICFP | **LiquidOps: Refinement-Verified NAND-Canonical Kernel for Data-Plane ISA Compilation** | | |
| | sovereign_entropy.tex | 394 | FM / CAV | **Sovereign Entropy: Formally Verified 0.20-Nat Bound for Deterministic Agent Outputs** | | |
| **GDR-9** - Nine-ISA kernel stack (CUDA, NASM, RISC-V, ARM, WASM, APL, Haskell, Lean 4, P4). Generalized delta rule + drain invariants. Cross-ISA equivalence proved in Lean 4. Target: SC/MLSys. | |
| **LiquidOps** - NAND-canonical verified compiler. LiquidHaskell refinement types enforce correctness end-to-end. P4 backend. Target: PLDI/ICFP. | |
| **Sovereign Entropy** - Lean 4 machine-checked proof: routing entropy H(alpha) <= 0.20 nats. SPARK Ada contract + ERE gate. Governs BURT-IMMA router and sovereign-memory-twin verdict threshold. Target: FM/CAV. | |
| **Zenodo (8 papers, published 2026-07-01)** - PIRTM, octonions, Coxeter/Weyl, PH-DAE, EmojiScript, Goldilocks, Resonance disclosure, DMZ F2 decomposition. DOIs in sovereign-engine-v2 README. | |
| --- | |
| ## License | |
| SnapKitty Tri-License | |
| ### 💼 Commercial License | |
| Snapkitty code is free and open under **AGPL-3.0** for open-source use. Building a commercial product or service? A **proprietary commercial license** from Snapkitty Collective LLC lets you ship this code without the AGPL's source-sharing and network-use obligations. | |
| **[→ Get a commercial license](mailto:A.parr@belespritdaccord.uk?subject=Commercial%20license:%20burt-imma)** · A.parr@belespritdaccord.uk | |