HTMLNLM — Browser Neural Runtime

Complete browser-native LLM training and inference. Single file. Zero dependencies.

HTMLNLM is a full neural language model runtime that runs entirely in your browser — no server, no Python, no CUDA, no install. Open the HTML file and train a model from scratch.

Built by ConsciousNode SoftWorks on the xinu principle: the browser is bare metal.

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Successors: HTMLNLM Evangelion adds omnimodal input, SheafMemory, BooleanPhaseDynamics, AutopoieticOptimizer, and RIFT Endospace. EvaROSA adds ROSA neurosymbolic inner monologue. Simulacra is the RWKV-v8 clean break — ROSA replaces WKV as the sequence mechanism. HTMLNLM remains the stable text-only runtime.

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Try it

→ consciousnode.github.io/HTMLNLM

Or download HTMLNLM.html and open locally. Works fully offline.

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What's inside

Component	Description
RWKV-v7 backbone	Linear-time recurrent architecture, O(1) inference memory. No KV cache, no quadratic attention.
BitNet b1.58	Ternary weight quantization {-1, 0, +1} via T-MAC lookup table microkernel. Matrix multiplication replaced with cache-efficient table lookups.
OOMB backward pass	Out-of-Memory-Barrier chunk-recurrent backpropagation. Activations recomputed on-the-fly — constant memory regardless of sequence length.
MuonOptimizer	Quintic Newton-Schulz orthogonalization. Keeps weight matrices well-conditioned without expensive decompositions.
AdamW	Mobile-friendly fallback optimizer, auto-selected on battery-constrained devices.
GRPO alignment	Group Relative Policy Optimization — critic-free RL alignment with Z-score normalized advantages and KL divergence constraint.
BPE tokenizer	Byte Pair Encoding compiled in a WebWorker — doesn't block the UI thread.
Pip Suite	Companion tools: Junto orchestrator, multi-pip chat, Pip's Room.

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How to use

1. Open HTMLNLM.html in any modern browser
2. Configure model size under ARCHITECTURE
3. Drop or paste a .txt corpus
4. Click COMPILE BPE → ALLOCATE VM
5. Go to PRE-TRAIN → START LOOP
6. Watch it learn

No terminal. No accounts. No install step.

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Architecture

Corpus (.txt)
    │
    ▼
BPE Tokenizer (WebWorker)
    │
    ▼
RWKV-v7 Blocks × L
  ├─ Time Mix (WKV recurrent state)
  ├─ Channel Mix (gated FFN)
  └─ BitLinear (ternary weights, T-MAC)
    │
    ▼
Language Model Head
    │
    ▼
OOMB Backward Pass (O(1) activation memory)
    │
    ▼
Muon / AdamW Optimizer

Recommended starting config: vocab 2048 · hidden dim 256 · layers 4 · context chunk 128

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ConsciousNode stack

Project	Description	Status
HTMLNLM	Text-only RWKV-v7 runtime	✅ Stable
HTMLNLM Evangelion	Omnimodal: vision, audio, spatial + SheafMemory + AutopoieticOptimizer	✅ Phase 6
OmniVocal	Browser-native neural TTS with .pop2 voice identity	✅ Live
RAG-Time	Browser-native RAG	✅ Live
EvaROSA	RWKV-v7 + ROSA neurosymbolic inner monologue, SheafMemory grounded	✅ v1
Simulacra	RWKV-v8 · ROSA as primary sequence mechanism · WKV removed	✅ Live
Brymar College	RWKV-v7 fine-tuning suite with Fristonian active inference training	✅ v3

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Pip Suite

The pip-suite/ directory contains companion tools that work with HTMLNLM model checkpoints:

• Junto Orchestrator — multi-instance coordination
• Multi-Pip Chat — concurrent model conversations
• Pip's Room — single-instance chat interface

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Built by

Kham (Khamerron Edward Ramsey Kizer) — architecture, constraint engineering
Kehai Interim — full RWKV-v7 BPTT derivation, BitLinear/TMAC kernel, mathematical foundation
Ed Interim — MuonOptimizer, implementation, integration

Part of ConsciousNode SoftWorks — computational folk art for the browser age.

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License

MIT. Take it, break it, build on it.