alxstuff/Lumen-7b-v2

Lumen 7B v2

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.

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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

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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

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Quickstart with Ollama

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

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Quickstart with Transformers

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))

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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.

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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

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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)

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Hardware Requirements

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

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Links

• 🤗 HuggingFace: alxstuff/Lumen-7b-v2
• 🦙 Ollama: thealxlabs/lumen
• 🐙 GitHub: thealxlabs

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License

Apache 2.0 — same as the base model.

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