๐ŸŒช๏ธ Typhoon V1 (Stable Diffusion 1.5 Edition)

"What began as Tornado V3 spun out into its own category-five situation."


๐Ÿงฌ Overview

Typhoon V1 for SD1.5 is a custom-trained model with a strong stylistic focus, built from scratch using carefully curated and tagged datasets. Initially meant as a continuation of Tornado, it soon veered off into its own trajectory โ€” aesthetically and technically โ€” and deserved a new name (and its own emotional baggage).

Despite the limitations of the SD1.5 architecture, Typhoon V1 inherits the stylization strengths of its SDXL sibling: sharp close-ups, expressive faces, confident eye rendering, and strong composition. It doesn't need ADetailer for faces and generally does a solid job on its own โ€” unless something weird sneaks in.

Just don't expect poetic prose prompts to work miracles โ€” this model responds best to short, tag-like prompts. That's because the dataset was trained using tagged images rather than natural language descriptions.


๐Ÿ”ง Development Notes

Typhoon was trained using a combination of full checkpoint training and LoRA modules, merged carefully one by one. Without local hardware capable of full-scale training, GPU rentals were required โ€” and with 3 out of 4 training runs failing, this project was not particularly budget-friendly.

Merging the LoRAs involved trial-and-error with strength tuning, weight adjustments, and the occasional expletive. To make things slightly less chaotic, I wrote a Python tool called the LoRA Strength & Epoch Analyser, available below:

Choosing a base model also proved tricky. Many SD1.5 bases are overly refined, biased, or neutered. I eventually settled on v1-5-pruned-emaonly.safetensors, which was the least problematic. That said, its limitations still show through.

Oh โ€” and yes, all training datasets were cropped to 512ร—512. This turned out to be a mistake, as it likely contributed to some of the model's anatomy and artifact issues. Iโ€™ll be correcting that for V2 when I scale the datasets properly. Eventually.


๐Ÿ–ผ๏ธ Sample Images

All images were generated without LoRAs, using the base Typhoon V1 model. Post-processing includes Hires Fix (if that qualifies as post-processing).

Settings:

  • Resolution: 512ร—768 or 576ร—768
  • Sampler: DPM++ 2M Karras (Euler and Euler A also work)
  • CFG: 7
  • Hires Fix:
    • Denoising strength: 0.7
    • Upscaler: Latent
    • Upscale by: 2
    • Hires CFG: 7
  • VAE: sd-vae-ft-ema

โš ๏ธ Legacy .vae.bin or .vae.pt files may cause washed-out or desaturated results. The official VAE or none at all is strongly recommended โ€” they yield identical (correct) results.


โš™๏ธ Prompting Tips

  • Trigger Words: None required
  • Prompting Style: Short, tag-style prompts preferred (e.g. 1girl, blue eyes, looking at viewer)
  • Natural Language: Avoid it โ€” this model thinks in tags, not sentences
  • ADetailer / Face Fixing: Not needed unless there's trouble with anatomy
  • Recommended Resolutions:
    • 512ร—768
    • 576ร—768
    • 640ร—832
      Avoid narrower resolutions like 512ร—640 unless you enjoy triple elbows and bonus fingers.

โš ๏ธ Limitations

  • NSFW: Base model is partially neutered. Typhoon tries its best, but results vary. When it clicks, it really works โ€” but don't expect consistency in that domain.
  • Anatomy & Artifacts: Can struggle at narrow aspect ratios. Use Hires Fix whenever possible.
  • Natural Language Prompts: Doesnโ€™t like them. Stick to short, structured prompts for best results.

๐Ÿ”’ License & Usage

  • โœ… Personal use: Absolutely
  • ๐Ÿšซ Do NOT upload this model to generation sites (e.g. online prompt tools or aggregators)
  • ๐Ÿšซ Do NOT merge this model into other models

Why? Typhoonโ€™s structure is the result of a very delicate merge process involving multiple LoRAs, adjusted manually. Combining it with other models will throw off its aesthetic balance and likely degrade quality. Plus, I spent way too much on GPU rentals and debugging for it to become someone's merge ingredient. Please respect the effort.


๐Ÿ”ฎ Future Work

Typhoon V2 is planned, and will address:

  • Properly scaled datasets (not just 512ร—512 crops)
  • Improved base model (if a truly vanilla one can be sourced)
  • Enhanced anatomy, reduced artifacts, and overall polish

Ongoing patch updates may be issued for V1 as more flaws are uncovered or edge cases appear.


๐ŸŒฉ๏ธ โ˜• Support the Storm

If you like what Iโ€™m building โ€” Typhoon, Tornado, the tools, the chaos โ€” and want to help keep it all spinning, consider supporting me on Ko-fi: https://ko-fi.com/raxephion

Every bit helps cover compute costs, caffeine, and the occasional "why is this broken?" meltdown. Thanks for keeping the storm alive.


Enjoy the storm. โ›ˆ๏ธ

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