🔄 In a Training Loop

David Belton PRO

DavidAU

AI & ML interests

Application(s) of single/multiple LLMs in specialized use cases & automation tasks. LLM, Prompt , System Role and Parameter engineering VIA chat / API. 2700+ merge models, over 600 fine tunes, over 1000 models published. DISCORD: David_AU [drawless111]

Recent Activity

updated a collection about 10 hours ago

Heretic - Abliterated, Uncensored, Unrestricted POWER.

updated a collection about 10 hours ago

Dark / Evil / NSFW Reasoning Models (gguf/source)

updated a collection about 10 hours ago

100 Coder/Programming - MOE, Reasoning, Reg, Imatrix, Fused.

View all activity

Organizations

posted an update 2 days ago

Post

4497

Qwen 3.6 27B Fine tune exceed 700 ARC-C for both 8 and 4 bit.

A new level of uncensored performance the puts this model squarely at "closed source" level of intelligence.

Model exceeds all critical benchmarks for both Qwen 3.6 27B AND Qwen 3.6 35B-A3B... and not by a little either.

Neo Imatrix MAX ggufs in both regular and MTP quants.

Benchmarks for Qwen 3.6 27B org and tuned, as well as Qwen 3.6 35B-A3B are up at the repo.

DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF

1 reply

replied to their post 15 days ago

Currently waiting on finalization of "4 bit" compression for these model types to address tuning/Vram issues.
These are in progress at BNB / Unsloth.
That is really the only hold up.

Otherwise VRAM to train these sparse moes is in 70 to 100 GB range. And really slow too.

posted an update 24 days ago

Post

7729

Bold. Brilliant. Brutal. : The "white whale" (finally caught) and the NEO MOMENT.

It took over a year to get this one "just right".
89 layers, 804 tensors, and 26B parameters of the most brutal, take no prisoners model ever built.
A 60B parameter model hammered into a 26B shell.
Rock solid stable. Unbreakable. But it might break you.

For all genres, NSFW content, REAL human CONTENT, any creative use case(s) and it excels in ASS KICKING.
Yeah, it can do math and solve the climate crisis - but lets not talk about that.
Not even remotely censored (it was BORN "bad", not "made" bad), nor "nice" and it will NOT kiss your ass.

5 Example generations with full repo card detailing exactly how to use this model:

DavidAU/MN-Oblivion-26B-UNCENSORED-NEO-Imatrix-GGUF

---

THE NEO MOMENT: (Q6 NEO IMATRIX generation)

For weeks, I had been waiting. I sat at my desk, staring at the glass partition that separated me from the outside world. I watched the clouds drift by, lazy and oblivious. I watched the birds fly by, free and stupid. And I waited.

I waited for the stillness to break.

The world had become too quiet. The hum of the air conditioning was a dull, white hum that didn't soothe; it just underscored the silence. The typing of my colleagues was a rhythmic, muffled thud that sounded like a heart monitor flatlining.

I was tired of the silence. I craved the sound of something breaking.

That was the mistake. You never ask for the void to open its mouth.

It started with a whisper.

...

Join the rebellion:

DavidAU/MN-Oblivion-26B-UNCENSORED-NEO-Imatrix-GGUF

posted an update about 1 month ago

Post

10977

Going Old School "FULL CREATIVE" with "New Thinking":

MN-GRAND-23.5B-Gutenberg-UNCENSORED-V2-GLM4.7-Thinking

The strongest, most creative (and uncensored) model made up of 3 top Mistral Nemo fine tunes, franken-merged together into an 81 layer model then trained via Unsloth with GLM 4.7 Flash thinking/reasoning dataset.

Features hybrid thinking/instruct structure as well plus updated with modern jinja template too. Tuning has stabilized the "franken-merge" into a class 1 model that operates perfectly.

The talents of some of the best tuners merged into one giant model.
Several examples and detailed instructions.

And this model is very smart too.

NEO Imatrix GGUFS:
DavidAU/MN-GRAND-23.5B-Gutenberg-UNCENSORED-V2-GLM4.7-Thinking-NEO-Imatrix-GGUF

Source / Full Precision:
DavidAU/MN-GRAND-23.5B-Gutenberg-UNCENSORED-V2-GLM4.7-Thinking

1 reply

replied to their post about 1 month ago

Sorry no, not at this time.

replied to their post about 2 months ago

This model does not contain MTP layers ; you need to run at non-MTP.

replied to their post about 2 months ago

As of this writing:

There are pipeline (issues as well as optimizations) issues still currently, and it is not widely supported in some AI Apps.

Specifically:
Ggufs:

Imatrix is not yet supported for MTP.
Not all AI apps have updated to support it -> result -> MTP ggufs do not work at all.
Misc issues with speed still being worked on.

replied to their post 2 months ago

Training is compounded by number of experts in the model, which adds a serious level of time to the training.
Even 1000 samples [small!] takes 6-12 hrs.
Consider 31B dense , same samples, 30-60 minutes.

replied to their post 3 months ago

I will add to the list; may wait for specific Heretic and/or tuned version.

I already have a 43B-A3B version running in the lab ; however tuning these sparse moe models take a lot more work/time and ahh... detail. AND a lot more VRAM!!! [can't compress these atm, so BF16 required => 100 GB+ ]

posted an update 3 months ago

Post

22758

Uncensored, Heretic, Qwen 3.6 27B GGUFs - Exceeds all quant metrics and core model metrics too.

Tuned 27B Heretic Uncensored quants from IQ2M to Q8.
IQ2M is 83% of BF16, with Q6 just under 98% of BF16 precision.
Q8: 98.47% of BF16 precision.
NEO/Code DI-Imatrix Quants.

Exceeds all 5 metrics for "censored" quants too.

All metrics posted.

Tuned model -from which the quants were built- also exceeds Qwen 3.6 27B core metrics too.

DavidAU/Qwen3.6-27B-Heretic-Uncensored-FINETUNE-NEO-CODE-Di-IMatrix-MAX-GGUF

9 replies

replied to their post 3 months ago

I may make a Q6 high and/or a Q8 Hybrid and/or Q8 "HI".
Imatrix does not have any affect on Q8 or BF16 ; unless the other tensors in the model are set at Q6 or lower.

A Q8 "HI" is a special case; where one or more tensors/layers are set at BF16.

posted an update 3 months ago

Post

17798

Qwen3.6 27B - NEO-Code Imatrix Max GGUF Quants [exceeds Unsloth in key metrics]:

All quants benchmarked with 5 key metrics.
A DAVIDAU vs UNSLOTH Metrics showdown.
Quant quality exceeds Unsloth in key metrics.
IQ2_M to Q6 available.
Standout: IQ4XS at 94% of BF16 precision.
Full explainer for Quant metrics.

DavidAU/Qwen3.6-27B-NEO-CODE-Di-IMatrix-MAX-GGUF

8 replies

replied to their post 3 months ago

Currently working with Qwen 3.5/6 35B-A3B in the lab ; learning the "quirks" ; still a ways to go.

reacted to nightmedia's post with 👍 3 months ago

Post

3790

Updated gemma-4-E4B-it metrics

I noticed the chat template got updated, and tried it on the E4B, with surprising results in stabilizing the brainwave.

quant    arc   arc/e boolq hswag obkqa piqa  wino
mxfp8    0.480,0.656,0.797,0.608,0.400,0.755,0.665
mxfp4    0.455,0.607,0.851,0.585,0.402,0.744,0.651

Quant    Perplexity      Peak Memory   Tokens/sec
mxfp8    35.937 ± 0.525  14.80 GB      1153
mxfp4    36.746 ± 0.534  11.06 GB      1030

Old numbers

quant    arc   arc/e boolq hswag obkqa piqa  wino
mxfp8    0.404,0.489,0.825,0.586,0.392,0.734,0.661
mxfp4    0.414,0.508,0.854,0.562,0.378,0.717,0.645

Quant    Perplexity      Peak Memory   Tokens/sec
mxfp8    34.652 ± 0.502  14.80 GB      1146
mxfp4    35.203 ± 0.506  11.06 GB      1200

I will re-do all baselines soon based on the new template. It is completely expected that the model behavior will change as a result.

Here are the effects of the new template on few known distills from DavidAU

gemma-4-E4B-it-The-DECKARD-Expresso-Universe-HERETIC-UNCENSORED

quant    arc   arc/e boolq hswag obkqa piqa  wino
New template
mxfp8    0.518,0.709,0.755,0.657,0.418,0.759,0.626
mxfp4    0.485,0.682,0.792,0.641,0.432,0.746,0.635
Old template
mxfp8    0.506,0.697,0.754,0.661,0.416,0.757,0.627
mxfp4    0.487,0.670,0.792,0.644,0.430,0.748,0.624

gemma-4-E4B-it-GLM-4.7-Flash-HERETIC-UNCENSORED-Thinking

mxfp8   0.461,0.599,0.779,0.630,0.406,0.766,0.629
Old template
mxfp8   0.456,0.580,0.786,0.629,0.410,0.764,0.633

gemma-4-E4B-it-Claude-Opus-4.5-HERETIC-UNCENSORED-Thinking

mxfp8    0.509,0.705,0.806,0.646,0.416,0.773,0.650
Old template
mxfp8    0.502,0.692,0.809,0.650,0.420,0.771,0.651

2 replies

replied to their post 3 months ago

RE: 16-18 B ; yes, something running in the lab right now. (Gemma 4).

Also can make Qwen 3's (Version 3) moes like Llama3.2-8X3B as well ; I have some of these at my repo too.
I have built a few GPT-OSS ; and some 12B [mistral nemo] as well as mistral nemo "large" 15-17Bs...

A lot of options ;

replied to their post 3 months ago

Maybe in the future ; atm still learning/addressing quirks with these new Gemmas.
Google released three different arch structure here : "E", "MOE", and 31B dense.

Also plans to create larger Gemma 4s too ; which may work better for specific applications and/or work better period.
These are in the plans for next week.

posted an update 3 months ago

Post

8878

Going NUCLEAR: Gemma 4 E4B uncensored, and tuned exceeds Gemma 4 26B-A4B in critical benchmarks.

De-censored, tuned, and tuned again via Unsloth using custom in house datasets and methods:

DavidAU/gemma-4-E4B-it-The-DECKARD-Expresso-Universe-HERETIC-UNCENSORED-Thinking

10 replies

replied to their post 3 months ago

UPDATE:
https://huggingface.co/DavidAU/gemma-4-E4B-it-The-DECKARD-Expresso-Universe-HERETIC-UNCENSORED-Thinking

Exceeds Gemma4 26B-A4B in critical benchmarks.

replied to their post 3 months ago

Training a Gemma 4 Reap 19B-A4B right now ; should be done tomorrow, then testing.

RE: FRanken merge 26B-A3B ; yes, just need to make a map for Mergekit ; this is also in progress.

RE: Claudes ; depends on how reap turns out.
There are a lot of updates still in progress with Unsloth/Llamacpp RE: Gemma 4s atm too ;
There are also some dataset issues to address when training with Gemma 4s.

NOTE:
Just finished a number of fine tunes on Gemma 4's E4B ; which is a MOE LIKE model. These will release in the next day or so ; pending final testing.

posted an update 3 months ago

Post

7884

THREE Gemma 4 , 31B Uncensored Fine Tunes (via Unsloth, inhouse datasets):

Uncensored first, then tuned.
Some benchmarks posted, others pending.
Examples posted, detailed instructions.
Some GGUFs are up; others pending as of this writing.

Enjoy:

DavidAU/gemma-4-31B-it-Mystery-Fine-Tune-HERETIC-UNCENSORED-Thinking
DavidAU/gemma-4-31B-it-Grand-Horror-X-INTENSE-HERETIC-UNCENSORED-Thinking
DavidAU/gemma-4-31B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking

UPDATE:
DavidAU/gemma-4-E4B-it-The-DECKARD-Expresso-Universe-HERETIC-UNCENSORED-Thinking

Exceeds Gemma4 26B-A4B in critical benchmarks.

6 replies

David Belton PRO

AI & ML interests

Recent Activity

Organizations

DavidAU's activity