Analyst 0.6B
A fine-tuned Qwen3-0.6B specialist for consulting-domain AI workflows. Built by AXe Technologies for production deployment in the Pulse platform.
Overview
Analyst 0.6B is a domain-tuned small language model designed for fast routing, intent classification, and structured call construction in consulting and professional services contexts. It runs entirely on-device — Apple Silicon Macs, edge servers, or any hardware that supports MLX or GGUF inference.
| Spec | Value |
|---|---|
| Parameters | 0.6B |
| Base Model | Qwen3-0.6B |
| Format | MLX (safetensors) |
| Training | LoRA fine-tune, single epoch |
| Context | 32K tokens |
| License | Apache 2.0 |
Intended Use
- Intent routing — classify user turns and dispatch to appropriate specialist models
- Call construction — parse natural language into structured function calls
- Domain drafting — generate consulting-domain responses with professional tone
- SQL generation — natural language to SQL for business analytics (basic queries)
Designed as the fast first-pass router in a multi-model specialist pipeline. Pairs well with larger models (3B, 7B) for complex reasoning tasks.
Quickstart
MLX (Apple Silicon)
from mlx_lm import load, generate
model, tokenizer = load("axetechnologies/analyst-0.6b")
prompt = "Classify this consulting request: 'Show me revenue by region for Q3'"
response = generate(model, tokenizer, prompt=prompt, max_tokens=256)
print(response)
llama.cpp / Ollama
Convert to GGUF for cross-platform inference:
# Using mlx_lm to convert, or download GGUF variants when available
python -m mlx_lm.convert --hf-path axetechnologies/analyst-0.6b --quantize q8_0
Training
- Method: LoRA (r=16, 16 target layers, alpha=32)
- Learning rate: 1e-4
- Batch size: 2-4
- Iterations: 400
- Epochs: 1 (single epoch — multi-epoch degrades instruction-tuned bases)
- Hardware: Apple Silicon (Mac Studio M2 Ultra, 64GB)
- Framework: MLX with mlx-lm
Training data is a curated mix of consulting-domain interactions: routing decisions, methodology checks, narrative interpretation, and NL-to-SQL pairs.
Limitations
- Optimized for consulting/professional services domain — general-purpose performance may trail the base model on out-of-domain tasks
- 0.6B parameter count means complex multi-step reasoning should be delegated to larger specialists
- English only
Model Family
| Model | Parameters | Role | Status |
|---|---|---|---|
| analyst-0.6b | 0.6B | Router / fast classifier | Released |
| analyst-3b | 3B | Call construction / parsing | Released |
| analyst-7b | 7B | Drafting / narrative | Released |
About
Built by AXe Technologies — sovereign AI infrastructure for regulated industries. All training and inference runs on owned hardware in Canada. No data leaves the perimeter.