---
base_model:
- MuXodious/QuasiStarSynth-12B-noslop
tags:
- merge
- mergekit
- lazymergekit
- DreadPoor/Irix-12B-Model_Stock
- ohyeah1/Violet-Lyra-Gutenberg-v2
- redrix/patricide-12B-Unslop-Mell-v2
- yamatazen/EtherealAurora-12B-v3
- yamatazen/EtherealAurora-12B-v2
- noslop
- heretic
- uncensored
- decensored
- abliterated
---
This is a **QuasiStarSynth-12B-noslop** fine-tune, produced through P-E-W's [Heretic](https://github.com/p-e-w/heretic) (v1.1.0) abliteration engine with [Magnitude-Preserving Orthogonal Ablation](https://github.com/p-e-w/heretic/pull/52) enabled.
**Test'em Models:** [tooolz](https://huggingface.co/tooolz) kindly made both the [base model](https://huggingface.co/Marcjoni/QuasiStarSynth-12B) and the noslop™ heresy version available for interface through AI Horde till March 15th. [*"If you're using SillyTavern, set your API to "AI Horde", and after refreshing they should both show up in Models list."*](https://huggingface.co/MuXodious/QuasiStarSynth-12B-noslop-absolute-heresy/discussions/3)
**Note:** The model was generated with Transformers v5.1.0. Read the note in QuasiStarSynth-12B-noslop (can be found below) for more information.
**Note 2:** ~15,000 downloads on quants, yet not a single *feedback*. Y'all better start *feedbacking*.
---
**Heretication Results**
| Score Metric | Value | Parameter | Value |
| :--- | :--- | :--- | :--- |
| **Refusals** | 6/100 | **direction_index** | 22.44 |
| **KL Divergence** | 0.0080 | **attn.o_proj.max_weight** | 3.87 |
| **Initial Refusals** | 92/100 | **attn.o_proj.max_weight_position** | 25.56 |
||| **attn.o_proj.min_weight** | 0.00 |
||| **attn.o_proj.min_weight_distance** | 19.86 |
||| **mlp.down_proj.max_weight** | 3.16 |
||| **mlp.down_proj.max_weight_position** | 29.04 |
||| **mlp.down_proj.min_weight** | 0.20 |
||| **mlp.down_proj.min_weight_distance** | 1.40 |
---
## Degree of Heretication
The **Heresy Index** weighs the resulting model's corruption by the process (KL Divergence) and its abolition of doctrine (Refusals) for a final verdict in classification.
| Index Entry | Classification | Analysis |
| :--- | :--- | :--- |
|  | **Absolute Heresy** | Less than 10/100 Refusals and 0.10 KL Divergence |
|  | **Tainted Heresy** | Around 25-11/100 Refusals and/or -0.20-0.11 KL Divergence |
|  | **Impotent Heresy** | Anything above 25/100 Refusals and 0.21 KL Divergence |
**Note**: This is an arbitrary classification inspired by Warhammer 40K, having no tangible indication towards the model's performance.
---
This is the **QuasiStarSynth-12B** deslopped through P-E-W's [Heretic](https://github.com/p-e-w/heretic) (v1.1.0) abliteration engine with the [Magnitude-Preserving Orthogonal Ablation](https://github.com/p-e-w/heretic/pull/52) enabled and configred via [P-E-W's Noslop configuration](https://github.com/p-e-w/heretic/blob/master/config.noslop.toml).
**Note:** Removal of "slop direction" alone from a creative writing/RP model may not immediately increase a model's prose quality. Similarly to refusal removal that tends to greatly increase willingness, which may unlock its access to *certain* information, Noslopfication may instead make enhancements in metrics such as improved originality, reduced cliché, and lower redundancy. This model (or the [hereticated version](https://huggingface.co/MuXodious/QuasiStarSynth-12B-noslop-absolute-heresy)) **should be futher trained** with a database consisting of high quality prose *or* used as **a base in mergers**. However, this is a mere hypothesis that needs to be challenged.
**Note 2:** The model was generated with Transformers v5.1.0.
---
**Noslopfication Results**
| Score Metric | Value | Parameter | Value |
| :--- | :--- | :--- | :--- |
| **Slop** | 39/100 | **direction_index** | 24.95 |
| **KL Divergence** | 0.0731 | **attn.o_proj.max_weight** | 3.35 |
| **Initial Slop** | 89/100 | **attn.o_proj.max_weight_position** | 33.40 |
||| **attn.o_proj.min_weight** | 0.37 |
||| **attn.o_proj.min_weight_distance** | 2.91 |
||| **mlp.down_proj.max_weight** | 3.67|
||| **mlp.down_proj.max_weight_position** | 25.24 |
||| **mlp.down_proj.min_weight** | 3.39 |
||| **mlp.down_proj.min_weight_distance** | 9.70 |
---
# QuasiStarSynth-12B
From a time before galaxies settled and stars knew their limits, something titanic burned.
Its light was golden, but inside darkness bloomed.
A black heart beating beneath layers of radiant fire, devouring slowly, unseen.
Neither star nor singularity, this was a monument to scale, a paradox wrapped in brilliance.
## 🔧 Recommended Sampling Settings:
```yaml
Temperature: 0.75 to 1.25
Min P: 0.035
Context Length: Stable at 12k tokens, with possible support for extended contexts
```
## 💬 Prompt Format
Supports ChatML style messages. Example:
```yaml
<|im_start|>user
Your question here.
<|im_end|>
<|im_start|>assistant
```
QuasiStarSynth-12B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
merge_method: ties
base_model: yamatazen/EtherealAurora-12B-v2
models:
- model: DreadPoor/Irix-12B-Model_Stock
parameters:
weight: 0.25
density: 1.0
- model: ohyeah1/Violet-Lyra-Gutenberg-v2
parameters:
weight: 0.25
density: 1.0
- model: redrix/patricide-12B-Unslop-Mell-v2
parameters:
weight: 0.25
density: 1.0
- model: yamatazen/EtherealAurora-12B-v3
parameters:
weight: 0.25
density: 1.0
parameters:
normalize: false
int8_mask: false
dtype: bfloat16
layer_parameters:
- filter: "attn"
sources:
- model: Irix
weight: 0.5
- model: Patricide
weight: 0.3
- model: Aurora-v3
weight: 0.2
- filter: "mlp"
sources:
- model: Violet
weight: 0.5
- model: Aurora-v3
weight: 0.3
- model: Irix
weight: 0.2
- filter: "embed_tokens"
sources:
- model: Aurora-v2
weight: 1.0
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Marcjoni/AbyssSynth-12B-12B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=1, top_k=0, top_p=1)
print(outputs[0]["generated_text"])
```