Instructions to use RMDWLLC/kaiju-coder-7-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RMDWLLC/kaiju-coder-7-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/kaiju-coder/models/Qwen3.6-27B") model = PeftModel.from_pretrained(base_model, "RMDWLLC/kaiju-coder-7-adapter") - Notebooks
- Google Colab
- Kaggle
Kaiju Coder 7 by Kiyomi - Data Provenance Draft
This draft records the current data boundary for release review.
Policy
Kaiju Coder training data must be legally usable for a commercial derivative model.
Allowed:
- RMDW-authored examples.
- RMDW-owned repository diffs and documentation.
- Human-reviewed examples created specifically for Kaiju.
- Public permissive data only when license review confirms compatibility.
Not allowed:
- Closed-model answers from OpenAI, Anthropic, Gemini, or similar services as supervised completions.
- Unreviewed customer data.
- Private customer code without consent.
- Secrets, tokens, credentials, cookies, or private keys.
- Unlicensed scraped code.
v0.1 Dataset Snapshot
- Total reviewed examples: 575
- Dataset build:
datasets/build/kaiju-sft-v0.1.jsonl - Candidate sources:
datasets/candidates/rmdw-git-patches.jsonldatasets/candidates/v0.1-safe-git-backlog.jsonldatasets/candidates/v0.1-file-level-git.jsonldatasets/candidates/v0.1-wiki-strategy-business-identity.jsonl
v1.7 Business-Owner Suite Addendum
- Date prepared: 2026-06-03
- Reviewed examples: 8
- Candidate file:
datasets/candidates/v1.7-rmdw-business-owner-suite.jsonl - Addendum-only SFT build:
datasets/build/kaiju-sft-v1.7-business-owner-suite.jsonl - Training SFT build:
datasets/build/kaiju-sft-v1.7-business-owner-oversampled.jsonl - Training config:
training/configs/qwen36-27b-lora-v1.7.example.json - v1.8 training config:
training/configs/qwen36-27b-lora-v1.8-business-owner.example.json - New task type:
business_suite - Source inventory:
release/SOURCE_INVENTORY.md, refreshed from GitHub source-of-truth repositories and the requested local RMDW wiki snapshot.
This addendum targets Kiyomi 7.7.7 style business-owner work: complete AI-company build packs, premium service websites, intake and CRM flows, sales follow-up, proposals, ROI dashboards, operator handbooks, and Workshop golden-run automations.
Every row includes:
source_repossource_pathsprovenance_notesreviewed: truelicense: RMDW-owned
For the v1.7 LoRA run, the 8 reviewed business-owner rows are oversampled 24 times by scripts/build_v17_business_owner_sft_dataset.py. Repeated rows receive unique IDs ending in __v17_business_repeat_NN and preserve the original source repository, source path, and provenance metadata.
Client-site repositories are used only as eval and generalized pattern sources unless a row is explicitly reviewed for training eligibility. Do not bulk-train on client-specific text, contact details, contracts, or private business data.
The local wiki path /Users/richardecholsai7/Documents/RMDW-Wiki is present but is not a git checkout. It is recorded as RMDW-Wiki-local, selective-reference-only, with credentials.md, customers.md, customers/, and raw/ excluded. The GitHub RichardEchols/rmdw-agent-wiki repo remains the authoritative wiki source for training/eval provenance unless a reviewer documents a local exception.
Category Mix
The v0.1 category gate passed:
- Website/UI: at least 75 examples
- Coding: at least 75 examples
- Debugging: at least 50 examples
- Automation: at least 50 examples
- Tool-use: at least 50 examples
- Strategy: at least 25 examples
- Business: at least 15 examples
- Identity: at least 10 examples
Release Review Checklist
Before public release:
- Re-run dataset validation.
- Re-run source inventory against the current GitHub source-of-truth SHAs.
- Spot-check examples for secrets and private data.
- Confirm client-site rows are generalized pattern examples or eval-only.
- Confirm closed-model outputs are not used as supervised completions.
- Record exact base model revision.
- Attach upstream license and notices.
- Attach eval summary.
- Document known limitations and unsafe use boundaries.