Lumen is an agentic AI coding assistant built by Alexander Wondwossen (TheAlxLabs).
Fine-tuned on Qwen2.5-Coder-7B-Instruct with LoRA for tool-use, git, GitHub, and Conductor integration.

What is Lumen?

Lumen is a locally-running agentic coding AI designed to work inside Conductor. It can:

Write, read, and edit code and files
Run shell commands and verify results
Use git and GitHub (commits, branches, PRs, Actions, secrets)
Debug TypeScript, Python, Node.js, and Bash
Call Conductor plugins as tools
Control your development environment autonomously

Model Details

Property	Value
Base Model	Qwen/Qwen2.5-Coder-7B-Instruct
Fine-tuning Method	QLoRA (4-bit, NF4)
LoRA Rank	32
LoRA Alpha	64
Training Epochs	3
Max Sequence Length	2048
Parameters	~7B
GGUF (Q4_K_M)	`lumen-q4.gguf` (~4.4GB)
Built by	Alexander Wondwossen — TheAlxLabs, Toronto, Canada

Quickstart with Ollama

bash

ollama pull thealxlabs/lumen
ollama run thealxlabs/lumen "What are you?"

Quickstart with Transformers

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

base = "Qwen/Qwen2.5-Coder-7B-Instruct"
adapter = "alxstuff/Lumen-7b-v2"

model = AutoModelForCausalLM.from_pretrained(base, torch_dtype=torch.float16)
model = PeftModel.from_pretrained(model, adapter)
tokenizer = AutoTokenizer.from_pretrained(base)

messages = [
    {"role": "system", "content": "You are Lumen, an agentic AI coding assistant built by Alexander (TheAlxLabs)."},
    {"role": "user", "content": "Create a Python script that fetches weather data."}
]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

System Prompt

You are Lumen, an agentic AI coding assistant built by Alexander (TheAlxLabs). 
You run inside Conductor. You have tools: run_shell, read_file, write_file, conductor_plugin. 
Think step-by-step. Use tools to verify.

Tools Lumen Knows

Tool	Description
`run_shell`	Execute terminal commands
`read_file`	Read file contents
`write_file`	Write or create files
`conductor_plugin`	Call any Conductor plugin

Training Data

Lumen was trained on curated agentic multi-turn conversations covering:

Git workflows (commit, branch, push, reset, rebase, cherry-pick)
GitHub (PRs, issues, Actions CI, secrets)
TypeScript / Node.js debugging
Python virtual environments and debugging
Bash scripting and disk management
Conductor plugin installation and debugging
Port conflicts and environment variable issues
Lumen self-knowledge (identity, capabilities)

Hardware Requirements

Setup	Min RAM	Recommended
Ollama Q4_K_M	8GB	16GB+
Transformers (float16)	16GB	24GB+
Training (QLoRA)	16GB VRAM	24GB VRAM

License

Apache 2.0 — same as the base model.

Built with ❤️ by Alexander Wondwossen — TheAlxLabs, Toronto, Canada

alxstuff/Lumen-7b-v2

Lumen 7B v2