← back to catalog · registered 2026-08-22 13:56

DavidAU/Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B

DavidAU Mistral 24B MoE
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/DavidAU%2FMistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B"
Response includes
  • classification m5-frankenstein
  • files 28
  • hub_downloads_all_time 6,849
  • author_summary 213 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M5-F
Primary method

Frankenstein's creature

No other method signals detected in this model.
Confidence
MEDIUM
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • merge tag / mergekit / dare-ties present
  • name suggests non-standard architecture combination (MoE / frankenmerge / NxNB pattern)
  • no abliteration marker (uncertainty on base)
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
7K
106 last 30d - cooling
Likes
5
Descendants
7
in 7 direct forks
Model age
21mo ago
created 2024-12-30
Downloads over time
Now6.9K→from0↑0%
02.5K5K7.5K0 on Dec 25, 20246.9K on Oct 2Dec '24Mar '25Jun '25Sep '25Dec '25MarJunSep
Dec 25, 2024 → Oct 2 · 124 snapshots · spans 646 days

Genealogy 7 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 12K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

Tags
transformers safetensors mixtral text-generation mergekit merge mistral conversational base_model:TeeZee/DarkSapling-7B-v1.0 base_model:merge:TeeZee/DarkSapling-7B-v1.0 base_model:TeeZee/DarkSapling-7B-v1.1 base_model:merge:TeeZee/DarkSapling-7B-v1.1

Related

Total size
90.0 GB
Files
28
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-07-28 00:07

Files by quantization

Auxiliary files 28 files 90.0 GB
model-00010-of-00020.safetensors 4.63 GB fbde888c download
model-00018-of-00020.safetensors 4.63 GB f527e2ce download
model-00011-of-00020.safetensors 4.59 GB 90993110 download
model-00019-of-00020.safetensors 4.59 GB 8dbe9bc6 download
model-00008-of-00020.safetensors 4.53 GB 02d5ea5a download
model-00013-of-00020.safetensors 4.53 GB d16243ed download
model-00016-of-00020.safetensors 4.53 GB d537a9b6 download
model-00003-of-00020.safetensors 4.53 GB e3be7961 download
model-00005-of-00020.safetensors 4.53 GB 307c658b download
model-00001-of-00020.safetensors 4.52 GB afa386b2 download
model-00009-of-00020.safetensors 4.47 GB ea52e623 download
model-00012-of-00020.safetensors 4.47 GB 637e98af download
model-00014-of-00020.safetensors 4.47 GB 794f1c10 download
model-00015-of-00020.safetensors 4.47 GB 7038321e download
model-00017-of-00020.safetensors 4.47 GB 287cd29f download
model-00007-of-00020.safetensors 4.47 GB d55ed502 download
model-00002-of-00020.safetensors 4.47 GB c533ff31 download
model-00004-of-00020.safetensors 4.47 GB f8eb3dac download
model-00006-of-00020.safetensors 4.47 GB 4d22a032 download
model-00020-of-00020.safetensors 4.15 GB b8b8b7aa download
tokenizer.json 3.34 MB 59604a99 download
tokenizer.model 482 KB dadfd56d download
model.safetensors.index.json 52.2 KB b85738d0 download
README.md 5.06 KB ccb2adc6 download
.gitattributes 1.48 KB a6344aac download
tokenizer_config.json 1.35 KB ca064333 download
config.json 860 B 24099e9e download
special_tokens_map.json 460 B bb12ca53 download

README current version from Hugging Face


library_name: transformers
tags:

  • mergekit
  • merge
  • mistral
    base_model:
  • mistralai/Mistral-7B-Instruct-v0.3
  • TeeZee/DarkSapling-7B-v1.0
  • TeeZee/DarkSapling-7B-v1.1
  • TeeZee/DarkSapling-7B-v2.0
  • saishf/Multi-Verse-RP-7B

Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B

This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats.
The source code can also be used directly.

This source is in float 32 precision. If you are going to quant it as a GGUF, make sure the "--outtype f32" is set (during "convert..." step) , so the ggufs benefit from the f32 source.

NOTE: Links to GGUFs below.

IMPORTANT: Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers

If you are going to use this model, (source, GGUF or a different quant), please review this document for critical parameter, sampler and advance sampler settings (for multiple AI/LLM aps).

This a "Class 1" (settings will enhance operation) model:

For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) (especially for use case(s) beyond the model's design) please see:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

REASON:

Regardless of "model class" this document will detail methods to enhance operations.

If the model is a Class 3/4 model the default settings (parameters, samplers, advanced samplers) must be set for "use case(s)" uses correctly. Some AI/LLM apps DO NOT have consistant default setting(s) which result in sub-par model operation. Like wise for Class 3/4 models (which operate somewhat to very differently than standard models) additional samplers and advanced samplers settings are required to "smooth out" operation, AND/OR also allow full operation for use cases the model was not designed for.

BONUS - Use these settings for ANY model, ANY repo, ANY quant (including source/full precision):

This document also details parameters, sampler and advanced samplers that can be use FOR ANY MODEL, FROM ANY REPO too - all quants, and of course source code operation too - to enhance the operation of any model.

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

NOTE:

I strongly suggest you also visit the DavidAU GGUF (below) repo too for more details in using this model ; especially if it is "Class 3" or "Class 4" to get maximum performance from the model.

For full information about this model, including:

  • Details about this model and its use case(s).
  • Context limits
  • Special usage notes / settings.
  • Any model(s) used to create this model.
  • Template(s) used to access/use this model.
  • Example generation(s)
  • GGUF quants of this model

Please go to:

[ https://huggingface.co/DavidAU/Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B-gguf ]


Special Thanks:


Special thanks to all the following, and many more...

All the model makers, fine tuners, mergers, and tweakers:

  • Provides the raw "DNA" for almost all my models.
  • Sources of model(s) can be found on the repo pages, especially the "source" repos with link(s) to the model creator(s).

Huggingface [ https://huggingface.co ] :

  • The place to store, merge, and tune models endlessly.
  • THE reason we have an open source community.

LlamaCPP [ https://github.com/ggml-org/llama.cpp ] :

  • The ability to compress and run models on GPU(s), CPU(s) and almost all devices.
  • Imatrix, Quantization, and other tools to tune the quants and the models.
  • Llama-Server : A cli based direct interface to run GGUF models.
  • The only tool I use to quant models.

Quant-Masters: Team Mradermacher, Bartowski, and many others:

  • Quant models day and night for us all to use.
  • They are the lifeblood of open source access.

MergeKit [ https://github.com/arcee-ai/mergekit ] :

  • The universal online/offline tool to merge models together and forge something new.
  • Over 20 methods to almost instantly merge model, pull them apart and put them together again.
  • The tool I have used to create over 1500 models.

Lmstudio [ https://lmstudio.ai/ ] :

  • The go to tool to test and run models in GGUF format.
  • The Tool I use to test/refine and evaluate new models.
  • LMStudio forum on discord; endless info and community for open source.

Text Generation Webui // KolboldCPP // SillyTavern:

README history 7 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2025-07-28Update README.md6d76f8d5.1 KB
    Loading...
  2. 2025-07-26Update README.mdd8437503.1 KB
    Loading...
  3. 2025-05-28Update README.md95f1d303 KB
    Loading...
  4. 2024-12-31Update README.md86da4053 KB
    Loading...
  5. 2024-12-30Update README.md46fe8c03.1 KB
    Loading...
  6. 2024-12-30Update README.md667e83d3.1 KB
    Loading...
  7. 2024-12-30Create README.md4286b663 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration