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alexokita/gemma4-style-step3000-GGUF
gemma4-style-step3000-GGUF is a text generation model from alexokita. Use it when you need the model to write or continue text. The card lists the license as gemma.
Merged Gemma 4 26B-A4B style-evaluator LoRA at checkpoint step 3000, converted to GGUF for llama.cpp / LM Studio.
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From the Hugging Face model README
Merged Gemma 4 26B-A4B style-evaluator LoRA at checkpoint step 3000, converted to GGUF for llama.cpp / LM Studio.
This is a prose style judge, not a fiction writer. Full intended use, training details, data sources, and the 14 Style-in-Fiction rubric metrics are documented on the companion LoRA card:
→ alexokita/gemma4-style-lora-step3000
| File | Quant | Size (approx) | Notes |
|---|---|---|---|
gemma4-style-step3000-q5_k_m.gguf | Q5_K_M | ~18 GB | Higher fidelity |
gemma4-style-step3000-q4_k_m.gguf | Q4_K_M | ~16 GB | Recommended for 24 GB GPUs |
F16 intermediate (~48 GB) was built locally for conversion and is not uploaded here.
style_profiles and short judgments over the 14 SiF-derived metricsNot for: open-ended novel writing.
From the Gemma 4 QAT model card: temperature 1.0, top_p 0.95, top_k 64, thinking off for JSON / classification.
| Item | Value |
|---|---|
| Base | Gemma 4 26B-A4B instruct QAT (unsloth/gemma-4-26B-A4B-it-qat-q4_0-unquantized) |
| Method | LoRA SFT (r=16, α=16) via Unsloth + TRL on DGX Spark |
| Steps | 3000 (best eval loss ≈ 2.378) |
| Data | ~430k / 48k style instruction pairs from Phase 2–3 labeled fiction |
| Conversion | merge LoRA → HF F16 → convert_hf_to_gguf.py → llama-quantize Q5_K_M / Q4_K_M |
Operationalized from Leech & Short, Style in Fiction (2nd ed.) in style_rubric.json:
lexical_complexity — LLM Pass 1lexical_density — computable (spaCy)register — LLM Pass 1sentence_complexity — LLM Pass 1sentence_length_mean — computablesubordination_ratio — computablefigurative_density — LLM Pass 1cohesion — LLM Pass 1dialogue_ratio — computablepov — LLM Pass 1mind_style — LLM Pass 2narrative_distance — LLM Pass 2free_indirect_discourse — LLM Pass 2tone — LLM Pass 2Labels: Phase 1 distilled the rubric from the book; Phase 2 classified prose with computables + multi-pass LLM + RAG; Phase 3 built SFT pairs. See the LoRA card for the full table and value enums.
Use of the base Gemma 4 weights is subject to the Gemma license.