Merging every training run into one "personality adapter" feels efficient. It is how you get a model that half-speaks operator voice, half-leaks NSFW caption grammar into a music brief.
The doctrine
- One adapter per lane — never melt private directives with brand captions
- Base model match — an 8B LoRA on a 3B base is cosplay
- Prove before live — temp-0 base vs adapter must differ; else the file is decoration
- Privacy routing — private corpora stay on private GPUs; scrubbed lanes may use free tiers
- Artifacts come home — if the zip never leaves Colab/Kaggle, it never existed
Example lane map
| Lane | Content | Train surface | |---|---|---| | dj-twin | operator voice, private directives | private only | | codeblack | historian / lineage | private only | | music | mastering doctrine, lyric pairs | free GPU if scrubbed | | hellcat | NSFW captions | private only | | beats / fulltwin | audio models | free GPU if scrubbed |
Serve path
Training logs are not production. Before anything is marked live:
- adapter file on home disk
- local serve path answers
- lane router selects scale per request (default scale 0)
- no secrets in train jsonl
Related
- Free compute discipline: Kaggle + twin LoRA
- Queue: Free GPU gauntlet
- $1 checklist pack: dajai shop — Twin LoRA Doctrine
FAQ
Can I share one adapter across brands for cost?
You can. You will also share voice contamination across brands. Cost savings are not free.
What's the fastest way to fake a live adapter?
Ship a zip you never pulled home and never proved against base. Don't do that.