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alxstuff/Lumen-7b-v2

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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Model Card

Lumen 7B v2

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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

Model Details

PropertyValue
Base ModelQwen/Qwen2.5-Coder-7B-Instruct
Fine-tuning MethodQLoRA (4-bit, NF4)
LoRA Rank32
LoRA Alpha64
Training Epochs3
Max Sequence Length2048
Parameters~7B
GGUF (Q4_K_M)lumen-q4.gguf (~4.4GB)
Built byAlexander 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

ToolDescription
run_shellExecute terminal commands
read_fileRead file contents
write_fileWrite or create files
conductor_pluginCall 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

SetupMin RAMRecommended
Ollama Q4KM8GB16GB+
Transformers (float16)16GB24GB+
Training (QLoRA)16GB VRAM24GB VRAM

Links


License

Apache 2.0 — same as the base model.


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