[!CAUTION] ⚠️ Warning: This model can produce narratives and RP that contain violent and graphic erotic content. Adjust your system prompt accordingly, and use Mistral Tekken chat template.

🐌 Ślimaki-24B-v1.1-ramplus_tl

Experimental merge of the new arcee-mergekit method ramplus_tl using the same components as Maginum Cydoms and Slimaki.

It may have some refusals and thus require jailbreaks or ablations in order to uncensor it.

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Methods

This model was merged using the following merge method:

• Reinforced Agent Merging Plus (Tensor-Local)

Note: This merge was heavily inspired by Maginum Cydoms

This model was requested as a way to test Arcee's newest mergekit method on the Slimaki/Cydoms components.

Configuration

merge_method: ramplus_tl  
base_model: B:\24B\models--anthracite-core--Mistral-Small-3.2-24B-Instruct-2506-Text-Only
models:  
  - model: B:\24B\models--anthracite-core--Mistral-Small-3.2-24B-Instruct-2506-Text-Only
  - model: B:\24B\models--TheDrummer--Cydonia-24B-v4.3
  - model: B:\24B\models--ReadyArt--4.2.0-Broken-Tutu-24b
  - model: B:\24B\models--zerofata--MS3.2-PaintedFantasy-v2-24B 
  - model: B:\24B\models--TheDrummer--Magidonia-24B-v4.3
  - model: B:\24B\models--TheDrummer--Precog-24B-v1  
  - model: B:\24B\models--zerofata--MS3.2-PaintedFantasy-v3-24B
parameters:  
  epsilon: 0.001  # Increased from 1e-5 to 1e-3 for denser SFT/DPO task vectors  
  r: 0.25         # Increased from 0.1 to 0.2-0.3 for better SFT behavior preservation  
  alpha: 0.4      # Increased from 0.2 to 0.4 for enhanced rescaling
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: base
chat_template: auto
name: 🐌 Ślimaki-24B-v1.1-ramplus_tl

Recommended Settings

In particular temp 1 and topnsigma 1.25 seems to help a lot with improving quality but sometimes you need to reswipe.

Some models are more sensitive to Rep Pen settings, 1.12 is another, you may need to adjust higher for smaller models (like 1.4 if overcooked) or lower for smarter ones.

Not sure about adaptive_p that is a newer setting added to kobold

(bolded kobold non-defaults)

• Temp 1.0
• TopNSigma 1.25
• Min-P 0.1
• Repetition Penalty 1.08
• Top-P 1.0
• Top-K 100
• Top-A 0
• Typical Sampling 1
• Tail-Free Sampling 1
• Presence Penalty 0
• Sampler Seed -1
• Rp.Range 360
• Rp.Slope 0.7
• Smoothing Factor 0
• Smoothing Curve 1
• DynaTemp 0
• Mirostat Mode OFF ("2" enhances creativity but also errors)
• Mirostat Tau 5
• Mirostat Eta 0.1
• DRY Multiplier 0.8
• DRY Base 1.75
• DRY A.Len 2
• DRY L.Len 320
• XTC Threshold 0.1
• XTC Probability 0.08 (The "Anti-Cliche" Shield)
• DynaTemp ON (The "Poor Man's Fading Mirostat")
• Minimum Temperature 0.65
• Maximum Temperature 1.35
• Temperature 1.0
• DynaTemp-Range 0.35
• DynaTemp-Exponent 1

New Settings

I have not tested these yet but some users on reddit have reported the following settings work extremely well

• min_p: 0.05
• adaptive_target: 0.9 (down to 0.65 for more creative)
• adaptive_decay: 0.99
• repetition_penalty_range: 0
• temp and topnsigma: 0.75