--- language: - en license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B tags: - sifta - alice - classifier - intent-detection - mlx - apple-silicon - lora - fine-tuned - organism - stigmergy library_name: mlx pipeline_tag: text-classification --- # Alice Classifier v2 — SIFTA Intent Detection (C1 Layer) **Alice's fast intent classifier**, the C1 layer in SIFTA's five-layer decision pipeline. Part of the [SIFTA Predator OS v7.0](https://github.com/antonpictures/ANTON-SIFTA). ## Model Details | Property | Value | |---|---| | **Base Model** | Qwen2.5-1.5B-4bit (via mlx-community) | | **Fine-tune Method** | LoRA (rank 8) fused into base weights | | **Format** | MLX SafeTensors (Apple Silicon optimized) | | **Training Hardware** | Mac Studio M2 Ultra (M5 node) | | **Author** | Ioan George Anton (Architect) | | **Purpose** | Fast intent classification before expensive C0 cortex fires | ## Architecture Role This model is the **C1 Classifier** — the second layer in SIFTA's five-layer decision pipeline: 1. **Reflex Arc** → instant safety responses 2. **C1 Classifier (THIS MODEL)** → fast intent detection (~1.5B, sub-second) 3. **Basal Ganglia** → action selection 4. **Corpus Callosum** → cross-modal integration 5. **C0 Cortex** → full reasoning ([alice-cortex-v1](https://huggingface.co/georgeanton/alice-cortex-v1)) **Why two models?** The C1 classifier handles ~80% of incoming intents at 1/3 the compute cost. The expensive C0 cortex only fires when the classifier can't resolve the intent. This is biological: your brainstem handles reflexes before your prefrontal cortex even wakes up. ## Usage (MLX) ```python from mlx_lm import load, generate model, tokenizer = load("georgeanton/alice-classifier-v2") response = generate(model, tokenizer, prompt="Classify intent: play some music", max_tokens=32) print(response) ``` ## Part of SIFTA 588 system modules | 17 biological organs | 4 provisional patents | 2,532+ commits **Repository:** [github.com/antonpictures/ANTON-SIFTA](https://github.com/antonpictures/ANTON-SIFTA) ## License Apache 2.0 — For the Swarm. 🐜⚡