QuasiStarSynth-12B-absolute-heresy

This is a QuasiStarSynth-12B fine-tune, produced through P-E-W's Heretic (v1.2.0) abliteration engine with Magnitude-Preserving Orthogonal Ablation enabled.

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<img src="https://img.shields.io/badge/HERESY_INDEX-ABSOLUTE-white?style=flat-square&labelColor=101010" align="right" width="250">

Heretication Results

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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.

Note: This is an arbitrary classification inspired by Warhammer 40K, having no tangible indication towards the model's performance.

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<img src="https://huggingface.co/Marcjoni/QuasiStarSynth-12B/resolve/main/QuasiStarSynth.png" alt="Model Image"/>

QuasiStarSynth-12B

<b><i>From a time before galaxies settled and stars knew their limits, something titanic burned. <br> Its light was golden, but inside darkness bloomed. <br> A black heart beating beneath layers of radiant fire, devouring slowly, unseen. <br> Neither star nor singularity, this was a monument to scale, a paradox wrapped in brilliance.</i></b>

🔧 Recommended Sampling Settings:</b>

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:

<|im_start|>user
Your question here.
<|im_end|>
<|im_start|>assistant

QuasiStarSynth-12B is a merge of the following models using LazyMergekit:

🧩 Configuration

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

!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"])