Text Generation
PEFT
Safetensors
English
kaiju-coder-7
lora
coding
local-ai
business
opencode
conversational
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
| license: apache-2.0 | |
| base_model: Qwen/Qwen3.6-27B | |
| language: | |
| - en | |
| library_name: peft | |
| pipeline_tag: text-generation | |
| tags: | |
| - kaiju-coder-7 | |
| - lora | |
| - coding | |
| - local-ai | |
| - business | |
| - opencode | |
| # Kaiju Coder 7 by Kiyomi - Adapter Model Card | |
|  | |
| This model card is for the LoRA adapter package, not a standalone base model. | |
| ## Summary | |
| Kaiju Coder 7 by Kiyomi is an RMDW/Kiyomi business-owner coding adapter trained on reviewed, RMDW-owned or RMDW-authored examples. It is designed for practical small-business build work: websites, proposals, intake/CRM flows, Stripe/payment implementation planning, reports, ROI dashboards, automations, operator handbooks, lead generation, sales follow-up, repo patches, and Kiyomi 7.7.7 style AI-company setup packs. | |
| The current release-candidate product path is: | |
| ```text | |
| Qwen3.6-27B base | |
| -> Kaiju v1.8 LoRA adapter | |
| -> merged full-model artifact for raw local serving | |
| -> Kaiju system prompt | |
| -> deterministic business-owner harnesses | |
| -> verifier/static checks | |
| ``` | |
| Do not describe this package as raw weights alone producing every final artifact. The deterministic harness is part of the tested product path. | |
| ## Base Model | |
| - Base model: `Qwen/Qwen3.6-27B` | |
| - Checked upstream revision: `6a9e13bd6fc8f0983b9b99948120bc37f49c13e9` | |
| - Upstream license metadata: `apache-2.0` | |
| - Upstream license copy: `release/upstream/qwen3.6-27b/LICENSE` | |
| Attribution wording: | |
| ```text | |
| Kaiju Coder 7 by Kiyomi is fine-tuned from Qwen under Apache 2.0. | |
| ``` | |
| Do not imply endorsement by Qwen, Alibaba, or upstream authors. | |
| ## Adapter | |
| - Adapter path: `runs/qwen36-27b-lora-v1.8-business-owner/adapter` | |
| - Adapter type: LoRA / PEFT | |
| - LoRA rank: `16` | |
| - LoRA alpha: `32` | |
| - LoRA dropout: `0.02` | |
| - Target modules: `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` | |
| - Trainable parameter count: approximately `79.7M` | |
| ## Merged Local Artifact | |
| - Remote merged path: `/home/richardecholsai5/kaiju-coder/models/Kaiju-Coder-Qwen3.6-27B-v1.8-merged` | |
| - Size: `51G` | |
| - Shards: `14` safetensor shards plus tokenizer/config sidecars | |
| - Served model name: `kaiju-coder-7` | |
| - Merge script: `scripts/run-gojira-b-qwen36-lora-merge.sh` | |
| - Serving script: `scripts/start-qwen36-merged-sglang.sh` | |
| ## Training | |
| - Dataset build: `datasets/build/kaiju-sft-v1.7-business-owner-oversampled.jsonl` | |
| - Reviewed candidate examples: `1,689` | |
| - SFT rows after controlled business-owner oversampling: `1,881` | |
| - Train examples: `1,769` | |
| - Eval examples: `112` | |
| - Training runtime: `11666.7564s` | |
| - Training loss: `0.9281658741335074` | |
| - Max training length: `2048` | |
| - Training config: `training/configs/qwen36-27b-lora-v1.8-business-owner.example.json` | |
| ## Data Provenance | |
| Training data is source-backed and RMDW-owned or RMDW-authored. Client-site repositories are used only as generalized pattern/eval sources unless explicitly reviewed for training eligibility. | |
| Relevant release files: | |
| - `release/SOURCE_INVENTORY.md` | |
| - `release/source-inventory.json` | |
| - `release/DATA_PROVENANCE_DRAFT.md` | |
| - `datasets/candidates/v1.7-rmdw-business-owner-suite.jsonl` | |
| Excluded from training: | |
| - Raw secrets, API keys, OAuth tokens, private keys, cookies, and credentials. | |
| - Closed-model answers from OpenAI, Anthropic, Gemini, or similar providers as supervised completions unless terms clearly allow it. | |
| - Private client data, customer notes, contracts, raw support logs, and client-specific website copy without explicit review and consent. | |
| ## Evaluation Snapshot | |
| Local product-path evidence: | |
| - Unit tests: `65` passing. | |
| - Full local RC smoke: passed. | |
| - Router hard harness: `23/23`. | |
| - Router static checks: `23/23`. | |
| - Business-suite prompts: `2/2`. | |
| - Local API harness: website and business-suite artifacts pass. | |
| Merged serving evidence: | |
| - Current endpoint: `http://127.0.0.1:18181/v1`, forwarding to vLLM | |
| bitsandbytes on Gojira B at `http://100.109.109.14:18084/v1` | |
| - Served model: `kaiju-coder-7` | |
| - Tested context: `16384` for the current OpenCode fast path. Historical | |
| SGLang benchmark evidence includes `32768`, but 32k should be freshly | |
| restarted and re-confirmed before being called the live default. | |
| - Probe: `1,155` visible chars in `60.17s`. | |
| - Proposal rerun: `1/1` paid-ready, `4.0/4.0`, `4,014` chars in `212.72s`. | |
| - Jah credits backend: `4.0/4.0`, `9,718` chars in `566.36s`. | |
| - OpenCode customer-readiness harness: `4/4` tasks passed, `28/28` required files written, including source/provenance and release-claim safety review. | |
| - vLLM nightly serving probe: passed at `16384` after `pandas` preinstall and | |
| `--language-model-only`. | |
| - Runtime-quantized vLLM bitsandbytes: current speed path; passed at `8192` | |
| and `16384`; 16k code patch completed in `11.3s`, and logs reported about | |
| `17.8 GiB` model memory. | |
| Known comparison caveat: | |
| - Dynamic SGLang LoRA serving is not release evidence for this adapter: adapter-name-only output can be base-equivalent, and corrected selector `qwen36-27b:kaiju_v18_business_owner` crashes with a fused-module LoRA buffer shape mismatch. | |
| - Do not claim raw-weight superiority until broader base-Qwen and GLM/current-production comparisons are complete. | |
| ## Limitations | |
| - Raw full-website generation has not yet passed the merged-model release sweep and should remain harness-first for paid delivery. | |
| - The deterministic harness remains the practical paid website workflow. | |
| - The adapter needs a strong app layer for file editing, tool use, auth, billing, rate limits, logging, and rollback. | |
| - Public HF upload and human review are complete for testing. Real customer | |
| paid charging still requires Stripe live-mode setup and controlled live | |
| payment verification. | |
| - Not intended for high-risk medical, legal, financial, or safety-critical decisions without expert review. | |