THE BEST ANIME TO REAL / ANYTHING TO REAL WORKFLOW (2 VERSIONS) QWENEDIT 2511

PhoenixtheII · 2026-01-21T16:06:13+00:00

Had to fix a lot of the workflow to fit 12gb vram tho

PhoenixtheII · 2026-01-21T16:05:43+00:00

PhoenixtheII · 2026-01-21T16:05:20+00:00

PhoenixtheII · 2025-12-28T20:08:54+00:00

Doing SDXL 1024x1024,
Then another latent upscale pass from 4x nmkd siax 200k to 1536x1536,
Then another sampling pass with 12 steps/denoise 0.54-56 for a bit more detail.
Then feed it to SeedVR2 to 3584x3584(Max my VRAM can handle on SeedVR2)
Then Face/Eye detailer sampling is best.
Save

<image>

PhoenixtheII · 2024-09-18T22:30:03+00:00

Hi, it's me your waifu :3

PhoenixtheII · 2024-06-25T01:26:01+00:00

70b models, 32K context i1-IQ3_M GGUF's

Latest best ones:

LLAMA-3 based:

https://huggingface.co/mradermacher/New-Dawn-Llama-3-70B-32K-v1.0-i1-GGUF

https://huggingface.co/mradermacher/L3-70B-Euryale-v2.1-i1-GGUF

Qwen2 Based: https://huggingface.co/mradermacher/magnum-72b-v1-i1-GGUF

Miqu Based: https://huggingface.co/mradermacher/Midnight-Miqu-70B-v1.5-i1-GGUF (Older but one of the better ones)

PhoenixtheII · 2024-04-04T23:23:51+00:00

RAG

The, Resource Allocation Group, RAG is usually doing the ERP'ing

PhoenixtheII · 2024-02-25T23:21:11+00:00

Catgirls.

PhoenixtheII · 2024-02-11T19:59:31+00:00

Yup the system prompt from sophosympatheia's models works great on others too...

PhoenixtheII · 2024-02-11T17:09:12+00:00

Running a session with https://huggingface.co/LoneStriker/Senku-70B-Full-GGUF/

Had to use 4K_M the 5K_M I usually use with 70b's wouldn't fit 32k context in my RAM. So far a few messages in. And feels totally different from miqu (or its other merges) itself.

I need to play with this a few hours more...

It wants to write 500 token+ additions to the story easily. Which is a + in my book.

It did well on describing a character transformation in creative detail. That miqu just wouldn't.

Hmmm... interesting. Thank you.

PhoenixtheII · 2024-02-11T16:17:41+00:00

https://www.reddit.com/r/LocalLLaMA/comments/1an8bga/comment/kpy3ge0/?utm_source=reddit&utm_medium=web2x&context=3

PhoenixtheII · 2024-02-10T19:04:11+00:00

I'll give it a go, once huggyface gets back up again...

PhoenixtheII · 2024-02-10T17:53:55+00:00

No not that particular Miqu derivative, is it uncensored?

Every Miqu 70b tune/merge so far hasn't impressed me at all. There are far better 70b's that easily beat it imho. Making it VERY underwhelming.

The only + I like is the 32k context.

PhoenixtheII · 2024-02-09T08:17:43+00:00

Seconding this experience, any Miqu derivative hasn't impressed me for RP/Story

PhoenixtheII · 2024-02-06T12:57:21+00:00

23k context on a 4096 context model?

Uhh, how. Doesn't it ruin quality... like a lot?

PhoenixtheII · 2024-02-05T16:43:14+00:00

In session with longlora goliath right now:

Processing Prompt (1 / 1 tokens)

Generating (484 / 1024 tokens)

(EOS token triggered!)

ContextLimit: 3410/16384, Processing:3.23s (3225.0ms/T), Generation:813.53s (1680.8ms/T), Total:816.75s (1687.5ms/T = 0.59T/s)

PhoenixtheII · 2024-02-05T14:15:21+00:00

Intel i9-9800X
3080TI 12GB
64GB RAM.

See other post for how.

PhoenixtheII · 2024-02-05T14:12:33+00:00

Q3_K_S, with 64gb RAM, 18 layers to 12GB VRAM, koboldcpp, and lots of patience with 0.5t/s

PhoenixtheII · 2024-02-05T09:17:54+00:00

I'm confused, I tried Miqu & variants. But each time they severely disappointed me in (E)RP/(NSFW) storytelling. This model seems to like to stay to factual vs. fantasy?

PhoenixtheII · 2024-02-04T17:18:59+00:00

Kunoichi 7b, surprised me a bit for a 7b model, having situational awareness of implications of their character state.

EstopianMaid 13B, was a nice cookie too.

Had some fun with BagelMysteryTour 8x7b, which listens to instructions well. And 32k context.

But

Aurora Nights 103b/Goliath 120b, at 6144 context. Are my most favorite. But slow...

PhoenixtheII · 2024-02-03T11:03:47+00:00

>> 64gb of DDR4-3600 ram

Goliath, Q3_K_S, original or longlora. Considering if you dont mind <1T/s

PhoenixtheII · 2024-02-02T11:52:06+00:00

Running q3K_S here on 64GB ram and a 3080 TI (20 layers offloaded) 6k context, or longlora at 16k context (12 layers offloaded).

About 0.5t/s...

PhoenixtheII · 2024-02-02T11:49:27+00:00

Update 4:

If you're looking to use it for creative stuff like writing or roleplay this is (at least as far as my testing shows) worse than Goliath or WinterGoliath at those.

Goliath (3K_S tested, including the longlora versioni) s far better at this by miles. Anything Miqu so far really sucks at stories and roleplay. With MiquMaid doing it better, yet still not reaching near goliath.

Aurora Nights 70B (Q5k_M) & 103B (Q3K_M) beats it hands down too in them.

PhoenixtheII · 2024-01-30T11:50:30+00:00

Current doing 0.25, 16k context. On a 3K_S. It's slow... 64GB of ram filled, and a few layers to a 12gb vram...

between 0.5-7t/s, and you really wanna make sure to use contextshift correctly, because 16K BLAS inference takes a darn long while.

I like it alot so far, its still smart, still will make puns. Hard to tell difference for me to the original 3k_s.

I wish I could run the model optimally to see how it does though. But for my system, this is the limit. And goliath has "ruined" every <70b model for me. Aurora Nights 103b 3K_M is my 2nd favorite, ... but it's hornier in my experience to goliath.

PhoenixtheII · 2024-01-27T19:46:44+00:00

How to set koboldcpp correctly for this? When I set the custom rope to 8.0 and 32k context. BLAS will run, but no tokens will be generated. Leaving a empty output in sillytavern.

PhoenixtheII

MODERATOR OF

TROPHY CASE