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metadata
title: SymbioSLM
emoji: 🧬
colorFrom: green
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
license: mit
tags:
  - julia
  - lux
  - slm
  - philosophy
  - openai-compatible
  - bpe
  - symbiogenesis
  - monarch-mixer
  - long-convolution
  - rmsnorm
  - swiglu

SymbioSLM

A Symbiogenesis decoder-only model trained on classical philosophy texts, implemented in Julia with Lux.jl. Features multi-organelle sequence mixing inspired by biological endosymbiosis (Margulis, 1967): three complementary "organelles" — CausalConv, MonarchMatrix, and LongConv — are fused via a learned per-channel OrganelleGate. Serves an OpenAI-compatible API with streaming support.

Endpoints

  • GET / — Health check and model info
  • GET /v1/models — List available models
  • POST /v1/chat/completions — Generate text (supports streaming, top-k, top-p)

Usage

# Non-streaming
curl -X POST https://your-space.hf.space/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "the nature of"}], "max_tokens": 200}'

# Streaming
curl -X POST https://your-space.hf.space/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "the nature of"}], "stream": true, "temperature": 0.7, "top_k": 40}'

Architecture

  • Model: ~5M params, 256d embed, 8 layers
  • Sequence mixing: 3 organelles per block fused via OrganelleGate:
    • CausalConv (local n-gram patterns, K=4)
    • MonarchMatrix (global structured mixing, single-head)
    • LongConv (global dense causal filter, K=256)
  • Gating: Per-channel softmax over organelles (learned specialization)
  • Tokenizer: BPE (2000 tokens)
  • Framework: Lux.jl (explicit parameter/state management)
  • Normalization: RMSNorm (pre-norm)
  • Feed-forward: SwiGLU activation
  • Weight tying: Shared embedding/output projection
  • Inference: CPU-only, no Lux dependency at runtime (pure NNlib)

Environment Variables

  • HF_REPO — HuggingFace model repo (default: LisaMegaWatts/SymbioSLM)
  • PORT — Server port (default: 7860)