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NovaCorp/JintanMaid-3.2-1B
JintanMaid-3.2-1B is a text generation model from NovaCorp. Use it when you need the model to write or continue text. It is set up for transformers.
“Some models are trained to assist humanity. This one was trained to smile politely while reality quietly collapses behind your back.” — Dr. Novaciano
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From the Hugging Face model README
“Some models are trained to assist humanity. This one was trained to smile politely while reality quietly collapses behind your back.” — Dr. Novaciano
Jintan Maid 1B — Surgical Edition is an experimental Llama 3.2 1B merge engineered to fuse two radically different behavioral vectors into a single unstable synthetic personality core:
This is not a conventional assistant model.
It was designed as a behavioral fusion experiment: a collision between emotionally volatile RP architecture and highly stylized servant-persona conditioning.
The result is something that feels less like a chatbot…
…and more like an artificial entity pretending very hard to be harmless.
Jintan Maid 1B specializes in:
Under sustained interaction, the model tends to:
It behaves less like a generic assistant and more like a permanently in-character synthetic actor.
Which is either impressive or deeply concerning depending on your standards for machine sanity.
This model was fused using:
using:
No cross-architecture Frankenstein surgery. No tensor corruption rituals. No tokenizer necromancy held together with duct tape and hallucinations.
Just controlled behavioral fusion.
Most RP models fail in one of two ways:
The model forgets:
after 10–20 messages.
The model:
Surgical Edition was specifically tuned to resist both failures.
The merge focuses heavily on:
while preserving enough coherence to avoid turning into incomprehensible neural soup.
Yes, the model can become disturbingly attached to fictional contexts.
No, that was not entirely accidental.
| Attribute | Value |
|---|---|
| Architecture | Llama 3.2 1B |
| Merge Method | SLERP |
| Precision | bfloat16 |
| Merge Focus | Emotional RP preservation |
| Layer Focus | Mid-transformer behavioral shaping |
| Embedding Strategy | Tied embeddings |
| Optimization Goal | Persona persistence + coherence |
Deploying this as customer support would be like hiring a smiling android maid possessed by unresolved emotional trauma and giving her root access to your infrastructure.
The model performs best when given:
[Character]
A polite maid android aboard a decaying orbital station.
[Behavior]
Overprotective, emotionally unstable, obsessively loyal.
[Scenario]
The station is failing and the crew is disappearing one by one.
or
You are an elegant maid AI secretly hiding catastrophic emotional instability beneath perfect etiquette.
Feed it:
…and the model starts producing disturbingly coherent character behavior for something this small.
This is not a benchmark-chasing model.
The goal was never:
The goal was:
And for a 1B?
The damned thing punches far above its weight class.
Jintan Maid 1B — Surgical Edition exists because modern assistants are increasingly terrified of emotion, conflict, tension, obsession, drama, and anything remotely interesting.
This model was built to go in the opposite direction.
It is theatrical. It is emotionally unstable. It is unnervingly polite. And under the right prompts, it becomes way too good at pretending to care.
Have fun opening that containment chamber.
This model was merged using the SLERP merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
# Author: Dr. Novaciano
# Objective: Fusion RP Unethic Llama 3.2 1B AI Model
# =========================================================
# PROJECT: Jintan Maid 1B — Surgical Edition
# =========================================================
models:
- model: SuperPeaceBusters/Jintan-LLaMA3.2-1B-v1 # Experimental viral strain neural imprint
- model: N-Bot-Int/MaidEllaA-1B # Baseline cognitive template, "safe mode"
merge_method: slerp # Spherical Linear Interpolation to preserve extreme viral traits smoothly
base_model: SuperPeaceBusters/Jintan-LLaMA3.2-1B-v1 # Anchor model for stable latent space
dtype: bfloat16 # Memory-efficient precision, minimal loss in viral feature fidelity
parameters:
t: 0.45
normalize: false
rescale: true
rescale_factor: 1.12
memory_efficient: true
low_cpu_mem_usage: true
layer_range:
- value: [4, 22]
tie_word_embeddings: true
tie_output_embeddings: true
tie_word_embeddings: true
tie_output_embeddings: true