axetechnologies/analyst-0.6b

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.