2stacks/my-resume-v2
Andrew Stanley Resume Q&A A small, hand-curated chat-format dataset of 122 question/answer pairs covering the professional background, career history, technical skills, certifications, and military service of Andrew Stanley, CTO / Chief Innovation Officer at SMS Data Products Group (McLean, VA). The dataset is purpose-built for two things: A working demonstration of an end-to-end LLM fine-tuning workflow — source document → synthetic Q&A generation → QLoRA fine-tune → GGUF… See the full description on the dataset page: https://huggingface.co/datasets/2stacks/my-resume-v2.
Andrew Stanley Resume Q&A
A small, hand-curated chat-format dataset of 122 question/answer pairs covering the professional background, career history, technical skills, certifications, and military service of Andrew Stanley, CTO / Chief Innovation Officer at SMS Data Products Group (McLean, VA).
The dataset is purpose-built for two things:
- A working demonstration of an end-to-end LLM fine-tuning workflow — source document → synthetic Q&A generation → QLoRA fine-tune → GGUF export → local Ollama deployment.
- A discoverable, queryable knowledge source about the author — so colleagues, recruiters, and collaborators can ask a fine-tuned local model "who is Andrew?" and get accurate, structured answers.
If you're a hiring manager or peer who landed here: feel free to clone the dataset, fine-tune your favorite base model, and chat with the result. The companion model card (forthcoming) walks through the exact training recipe.
Dataset details
Schema
Each line is a single JSON object with one user turn and one assistant turn:
{"messages": [
{"role": "user", "content": "Where does Andrew work?"},
{"role": "assistant", "content": "Andrew works at SMS Data Products Group, headquartered in McLean, VA. ..."}
]}This format drops in directly to the chat templates used by Qwen3, Llama-3, Mistral-Instruct, and most modern instruction-tuned bases — no preprocessing required for TRL SFTTrainer, Unsloth, or Axolotl.
Topic coverage
- Identity, current role, location, contact (email only)
- Career timeline (SMS Data Products Group, prior roles)
- Sector experience (Defense, Federal, commercial)
- Technical skills: hybrid multi-cloud (AWS, Azure), DevSecOps, CI/CD, Zero Trust, AI/ML enablement
- Certifications: AWS AI Practitioner, AWS Solutions Architect Associate, AWS Cloud Practitioner
- Education: BS in Information Technology / Security, George Mason University (2006)
- Military service: U.S. Army Signal Officer, Afghanistan deployment 2008–09
- Security clearance: Active U.S. government clearance (details available upon request)
- Leadership philosophy and engineering management approach
How this dataset was built
- Started with Andrew's current resume (PDF) and LinkedIn export as the source of truth.
- Drafted question/answer pairs by topic cluster — biographical, role-specific, skills, certifications, military, leadership.
- Wrote each answer to be self-contained (no anaphora across pairs) so the model learns durable facts rather than dialogue continuity.
- Sanity-checked for PII: phone number scrubbed, only a public-facing email retained.
- Validated JSONL well-formedness and chat-template compatibility with a Qwen3-8B tokenizer.
Intended use
- Primary: fine-tune a small/medium open-weight chat model (e.g. Qwen3-8B, Llama-3.1-8B-Instruct, Mistral-7B-Instruct) so it can answer biographical questions about Andrew Stanley.
- Secondary: reference example for anyone learning QLoRA / instruction tuning who wants a tiny, self-contained dataset to iterate on.
Reference training recipe
The author's reference run used:
A companion model trained with this exact recipe is published at `2stacks/qwen3-8b-andrew-resume-v2` (GGUF Q4KM, drop-in for Ollama / llama.cpp).
Limitations and biases
- Tiny (122 rows). This is a personal-knowledge fine-tune, not a general capability dataset. Expect heavy overfit to these exact phrasings unless paired with a broader instruction-following dataset during training.
- Single subject. All assistant outputs concern one real person. Models trained solely on this set will confidently answer about Andrew Stanley and have no grounding for any other entity.
- Self-curated. The author wrote the answers about himself, so framing reflects how he wants to be described professionally. Treat it as a polished bio, not an independent biography.
- English-only.
- Snapshot in time. Reflects career state as of May 2026; will go stale.
Personal information
The dataset intentionally contains:
- Full name, current employer, city of residence (Bethesda, MD)
- Public-facing email:
2stacks@2stacks.net - Public career history mirroring the author's LinkedIn profile
The dataset intentionally does not contain:
- Personal phone number
- Home street address
- Government / clearance details beyond confirming an active clearance is held
- Family member information
The subject (Andrew Stanley) is the publisher and consents to release of this information under CC-BY-4.0.
Citation
@dataset{stanley_resume_qa_2026,
author = {Stanley, Andrew},
title = {Andrew Stanley Resume Q\&A},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/2stacks/my-resume-v2}
}Contact
- Email:
2stacks@2stacks.net - Hugging Face: @2stacks
