spoomplesmaxx-27b-4500

SpoomplesMaxx 27B 4500 — SFT (Olivia + RP-Reasoning)

SpoomplesMaxx SFT is a supervised fine-tuning adapter trained on top of aimeri/spoomplesmaxx-base-gemma3-27b-4500 — the end-run candidate checkpoint from the SpoomplesMaxx CPT run on Gemma 3 27B PT.

This stage teaches system-prompt following, persona consistency, and structured narrative reasoning for collaborative fiction and character roleplay. It is implemented as a LoRA adapter and requires the CPT base to run.

This model was trained on checkpoint 4500 out of ~5700 steps. A future run of the completed CPT model will follow.

Part of the SpoomplesMaxx project — a hobbyist ML research effort focused on creative writing and roleplay capability in open base models.

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Model Details

Pipeline position

google/gemma-3-27b-pt

↓

CPT (spoomplesmaxx-base-gemma3-27b-4500) ↓ SFT ← you are here ↓ DPO (planned)

Uses

Direct Use

This model is suitable for:

• Character roleplay and collaborative fiction with persistent persona
• System-prompt-driven character following (multi-character mode-switching)
• Structured narrative generation with explicit scene/continuity state tracking
• Multilingual creative writing in English and Brazilian Portuguese

Load with a chat-capable inference frontend (e.g. SillyTavern, Oobabooga, llama.cpp with a compatible template).

Downstream Use

Intended as an intermediate checkpoint in the full pipeline. A DPO alignment stage targeting preference learning over character voice and narrative consistency is planned.

Can also serve as a base for further LoRA fine-tuning on custom character datasets or domain-specific creative writing corpora.

Out-of-Scope Use

• General-purpose instruction following or assistant tasks — the model is optimized for character roleplay and creative writing, not factual Q&A or task completion
• Production deployment without further alignment — this is a hobbyist research artifact
• Safety-critical applications — the base CPT model is uncensored; this SFT stage does not add safety alignment

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Training Details

Training Data

Two datasets were used:

Olivia Costa — the primary persona in the Olivia dataset — is warm but direct, anti-sycophantic, and trained to present as human. She serves as both the default persona and the calibration signal for tone and voice across the character library.

Training Procedure

SFT was performed on the CPT checkpoint using LoRA, with vision components frozen (inherited from base). Training targets text layers only.

Training Hyperparameters

• Training regime: bf16 mixed precision
• Adapter type: LoRA
• Training framework: TRL + Unsloth

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Evaluation

No formal benchmarks have been run on this adapter. Evaluation is qualitative — persona consistency across multi-turn conversations, system-prompt adherence across character cards, and narrative coherence in the rp-reasoning traces.

If you run evaluations or have qualitative findings, please open a discussion.

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Project History

Earlier CPT runs on SmolLM3 3B, GLM-4-32B, and Qwen3-14B are archived or available separately. Gemma 3 27B was selected for this stage based on superior out-of-the-box creative writing quality and multilingual coverage.

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Model Card Authors

• aimeri

Model Card Contact

Open a discussion on the repository page.