--base1

To be completely honest, I trained this model on this specific caption format while I was pretty drunk, so it is what it is lol. I'm not even entirely sure how it works under the hood, and I didn't have enough time to thoroughly test everything out. Also, please don't come at me calling me retarded or saying "it doesn't work like that" - just chill, I'm just experimenting here. Hopefully, you guys can help me with that and test.

Anyway, here is a mini-guide on how it's supposed to work (written by Gemini):

To achieve maximum realism, analog grit, or authentic casual smartphone aesthetics, you should follow the exact prompt structure the model was trained on.

📐 The Prompt Formula:

[Prefix Tags] + [Natural Language Description] + [Suffix Tags & Score]

1. Prefix Tags (The Setup): Set the camera type, lighting, safety, and shot style at the very beginning.

2. Core Description (The Scene): Describe the subject, clothing, pose, and background using natural English sentences (avoid messy tag-soup).

3. Suffix Tags (The Quality & Era): Close your prompt with the simulated year of the photo and the quality score.

📋 KEYWORDS TO COPY-PASTE

1. Camera & Tech Prefixes:

• @smartphone_photo — Casual, modern mobile look with subtle computational processing.

• @compact_digital_photo — Early 2000s "point-and-shoot" digicam vibe.

• @film_photo — Authentic analog look with rich organic textures and grain.

• @vhs_screencap — Retro video tape style with scanlines.

• @dslr_photo — Clean, professional camera rendering.

2. Lighting & Style Prefixes:

• @available_light — Soft, natural indoor/outdoor daylight.

• @direct_flash — Harsh, flat flash (perfect for late-night party vibes or digicam looks).

• @candid_photo — Caught-on-camera, unposed, natural moments.

• @posed_photo — Deliberate posing.

• @mirror_reflection — Perfect for mirror selfies.

• @underexposed / @overexposed — For dramatic low-light or high-contrast shots.

3. Safety Blocks:

• @sfw or @nsfw (choose depending on your target generation)

4. Era & Quality Suffixes (Put at the very end!):

• Years: @1995, @2000, @2005, @2010, @2020, @2025

• Scores: score_5, score_6, score_7, score_8, score_9 (can be used in negative)

💡 Tip: Use score_8 or score_9 for high definition and clean details. Use score_6 or score_7 combined with @smartphone_photo or @compact_digital_photo if you want a grittier, intentionally imperfect lo-fi look!

📸 EXAMPLE PROMPTS

• Modern Smartphone Selfie:

@smartphone_photo @sfw @amateur_photo @candid_photo @available_light A close-up portrait selfie of a 20-year-old woman with neon green hair and heavy eyeliner. She is looking at the camera with a neutral expression. The background is a blurry minimalist bedroom. @2025 score_8

• Retro Digicam Flash (Vibe from 2005):

@compact_digital_photo @sfw @amateur_photo @posed_photo @direct_flash An overexposed snapshot of a young woman posing in a cluttered room at night. Harsh flash lighting, red-eye effect, visible digital noise, and washed-out colors. @2005 score_7

• Analog Film Portrait (Cosplay):

@film_photo @sfw @amateur_photo @candid_photo @available_light A medium shot of a young woman cosplaying Princess Zelda, sitting inside a

P.S.: still WIP, i plan extend dataset and train more

--preview3

I'm also sharing a new experimental version of UltraReal FineTune Anima, this time trained on Anima_preview3.

This version was made because several people asked for a preview3-based release. In some cases it can produce better results than the preview1 version, especially depending on the prompt, but in other cases preview1 may still look better or behave more consistently.

So I don't really consider this a strict upgrade — it's more like an alternative version. Try both and use whichever one works better for your workflow and your prompts.

Model Features:

• Based on Anima_preview3

• Trained in the same way as preview1 release

• Still highly prompt-sensitive

• Some improvements in certain styles and generations

• Some possible regressions compared to the preview1 version

• Still Experimental / WIP

Special thanks to the Reddit donor who supported the project — your donation was one of the reasons I decided to retrain this for preview3 as well.

P.S.: in my flow i use custom sampler and scheduler, u can take it here https://github.com/WASasquatch/RES4SHO

--preview1

Hey everyone. I'm sharing my new experimental full finetune of the Anima_Preview1.

For this version, I collected a completely new dataset from scratch - it's entirely different from the one I used for my Flux.1 finetune.

Model Features:

🎛️ Highly Prompt-Sensitive: The stylistic range is quite diverse, but the final output relies heavily on your specific prompting.

📸 Analog & Digital Aesthetics: It can produce a wide variety of looks, from distinct analog grain to "high-quality" digital photos (well, as high-quality as it gets for a 1MP retro resolution).

⚡ Optimized: I've included Q8 and Q6_K_M quants for easier inference.

Honestly, I really love the image quality you can squeeze out of such a small model. However, this is still very much a WIP (Work in Progress).

I would love to hear your feedback and see your generations.

Also, NSFW capabilities weren't harmed