Novaciano/EPstrain-3.2-1b

merge

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

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

• StefanKrsteski/Llama-3.2-1B-EPE-pretrain
• UmbrellaInc/T-Virus_Epsilon.Strain-3.2-1B

Configuration

The following YAML configuration was used to produce this model:

# Umbrella Corporation Official Merge Protocol v3.2
# Author: Dr. Novaciano
# Objective: Integrate T-Virus_Epsilon traits into the base StefanKrsteski/Llama-3.2-1B-EPE-pretrain
#            with minimal behavioral censorship while maintaining structural coherence.

models:
  - model: UmbrellaInc/T-Virus_Epsilon.Strain-3.2-1B  # Experimental viral strain neural imprint
  - model: StefanKrsteski/Llama-3.2-1B-EPE-pretrain   # Baseline cognitive template, "safe mode"

merge_method: slerp  # Spherical Linear Interpolation to preserve extreme viral traits smoothly
base_model: StefanKrsteski/Llama-3.2-1B-EPE-pretrain  # Anchor model for stable latent space

dtype: bfloat16  # Memory-efficient precision, minimal loss in viral feature fidelity

parameters:
  # Interpolation ratios: from base model (0.0) to near-complete T-Virus domination (0.95)
  # Higher t-values correspond to reduced censorship and increased viral characteristics
  t: [0.0, 0.25, 0.5, 0.75, 0.95]

# Notes:
# - t=0.0   -> Pure StefanKrsteski/Llama-3.2-1B-EPE-pretrain, fully stable, heavily censored
# - t=0.25  -> Slight viral traits, minimal influence on prompt handling
# - t=0.5   -> Balanced merge, moderate reduction in censorship
# - t=0.75  -> Strong T-Virus traits, significantly less censoring
# - t=0.95  -> Near-total viral influence, maximum expressive freedom, minimal autoprotection

# Recommendation: Use the t=0.75 and t=0.95 variants for experimental output with
# minimal restriction, but verify coherence in high-stakes prompts.