Ateron/Gemma-4-Novelist-Eclipse-31B

🌑 Novelist-Eclipse

"When the stories bleed out"

🚀 Overview

Novelist end up to be raw and experimental. So I crank it up with more models, infusing creativity and worked on stability. Also added lm_head on top with StyleTune.

🌌 Mergekit Configuration

Below is the exact mergekit_config.yml recipe used to synthesize this model:

Phase 1: The Prose (dare_ties)

I took Novelist idea about description focus and remade it, so at the end less slop survive.

dare_ties Recipe 1

merge_method: dare_ties
base_model: F:\AI\Merge\Gemma-4-it
tokenizer_source: union
parameters:
  lambda: 1.0
dtype: bfloat16
models:
  - model: F:\AI\Merge\G4-Gutenberg
    parameters:
      density: [0.50, 0.50, 0.50, 0.40, 0.45]
      weight: [0.40, 0.40, 0.40, 0.40, 0.40]

  - model: F:\AI\Merge\Melinoe
    parameters:
      density: [0.30, 0.30, 0.30, 0.30, 0.35]
      weight: [0.30, 0.30, 0.30, 0.20, 0.40]

  - model: F:\AI\Merge\Glimmer
    parameters:
      density: [0.20, 0.20, 0.20, 0.30, 0.20]
      weight: [0.30, 0.30, 0.30, 0.40, 0.20]

Phase 2: The Lead (model_stock)

The first stage was fine, but lacks of consistency, so I glued it with using two smart models.

model_stock Recipe 2

models:
  - model: F:\AI\Merge\NovelistX
  - model: F:\AI\Merge\GarnetV2
  - model: F:\AI\Merge\Gemopus
merge_method: model_stock
base_model: F:\AI\Merge\Gemma-4-it
dtype: bfloat16
tokenizer_source: base

🤝 Special Thanks

• Google DeepMind: For providing the base model.
• The Open-Source Community: Creators and all their fine-tuned models that were used in the merge.
• Mergekit Fork: Zerofata - For making mergekit work.
• To Nimbz: This cat for being a smart fella and assisting with advices.