Naphula_StormSeeker-24B-v1_EXL3

Source model

StormSeeker-24B-v1 by Naphula

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Provided quantized models

ExLlamaV3: release v0.0.18

Requirements: A python installation with huggingface-hub module to use CLI.

Licensing

License detected: apache-2.0

The license for the provided quantized models is inherited from the source model (which incorporates the license of its original base model). For definitive licensing information, please refer first to the page of the source or base models. File and page backups of the source model are provided below.

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Backups

Date: 13.01.2026

Source files

<details> <summary>Source page (click to expand)</summary>

[!CAUTION] <span style="color:red; font-weight:bold">⚠️ Warning:</span> This model can produce narratives and RP that contain violent and graphic erotic content. Adjust your system prompt accordingly. Also, use Mistral non-Tekken for best results.

StormSeeker 24B v1

This took 14 hours to merge using a custom method.

According to the audit, Loki, PaintedFantasy, and Hearthfire had a bit more influence than the other 3 models, but nothing was "drowned out".

The model is rather uncensored even without ablation and responds to some (not all) harmful prompt without refusals or jailbreaks, so a light jailbreak works effectively to bypass most censorship.

For ablations you can use this https://huggingface.co/Naphula/StormSeeker-24B-v1-MPOA-Adapter

The model is smarter with Mistral Non-Tekken:

• StormSeeker v1 [Non-Tekken] | 8867
• StormSeeker v1 [Tekken] | 6933

models: 
  - model: A:\LLM\.cache\huggingface\hub\!models--CrucibleLab--M3.2-24B-Loki-V2
  - model: A:\LLM\.cache\huggingface\hub\!models--LatitudeGames--Hearthfire-24B
  - model: A:\LLM\.cache\huggingface\hub\!models--PocketDoc--Dans-PersonalityEngine-V1.3.0-24b
  - model: A:\LLM\.cache\huggingface\hub\!models--ReadyArt--Dark-Nexus-24B-v2.0
  - model: A:\LLM\.cache\huggingface\hub\!models--TheDrummer--Cydonia-24B-v4.3
  - model: A:\LLM\.cache\huggingface\hub\!models--zerofata--MS3.2-PaintedFantasy-v3-24B
merge_method: flux # version 5, Y6 config
parameters:
  resume_path: "A:/mergekit-main/Storm_Cache"
  tol: 1e-9
  max_iter: 1005 #maximum BF16 fidelity
  kappa: 0.8
  eta: 0.9
  auto_buffer: true
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: union
chat_template: auto
name: StormSeeker-24B-v1

According to the LLM, quantizations made from merges with merge_method: flux benefit greatly from the smaller block sizes of IQ4_NL, saying it should be on par with or slightly better than Q6_K, despite having higher perplexity. Note that this doesn't apply to merges made using standard methods like model_stock or karcher, and this claim has not yet been empirically verified.

Due to space/time constraints I am only uploading the following GGUFs:

• IQ4_NL
• Q6_K
• Q8_K_XL

I recommend these pages for other quantizations:

• team mradermacher for GGUF (usually has IQ4_XS)
• DeathGodlike and ArtusDev for EXL3
• McG-221 for MLX

FLUX Saturation Chart

Iterations required to fully saturate the information density ceiling of the quant.

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