Create README.md

README.md

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+---
+license: creativeml-openrail-m
+base_model:
+- stable-diffusion-v1-5/stable-diffusion-v1-5
+library_name: diffusers
+---
+
+# 🌪️ Typhoon V2 (Stable Diffusion 1.5 Edition)
+
+> _"Still SD1.5. Still cursed. But at least now it understands limbs."_
+
+---
+
+## 🧬 Overview
+
+Typhoon V2 is the long-overdue upgrade to Typhoon V1, trained for SD1.5 using smarter techniques, cleaner data, and a few hard-earned lessons from the first version. The result? More control, better anatomy, stronger stylization — and fewer existential crises per batch.
+
+It builds on the core identity of V1 (tag-based prompts, no trigger words, bold composition) but addresses its flaws head-on: warped limbs, prompt misfires, and the occasional brush with the uncanny.
+
+V2 plays much nicer with short prompts, handles faces even better than before, and generally won’t lose its mind when asked for basic body parts. Still no poetic-prose magic, though — this one *also* thinks in tags.
+
+---
+
+## 🔧 Development Notes
+
+Typhoon V2 was trained from scratch again, but this time with properly scaled datasets (no more 512×512-only crops) and aspect-ratio-aware augmentation. The architecture is still SD1.5, but the dataset strategy and training parameters got a much-needed overhaul.
+
+Training was done on rented A100s — because, apparently, learning costs pain. Dataset prep was completely redone, with better captions, refined tag filtering, and entirely new sets focused on pose coverage, negative regularization, and structural accuracy.
+
+Merging? None this time — this is a native checkpoint. No LoRA layering, no weight juggling. Just clean, consolidated training. (Still used my analysis tools, though — because mistakes are expensive.)
+
+🛠️ Tools used during development:
+
+- [LoRA Strength Analyser](https://github.com/Raxephion/loRA-Strength-Analyser)  
+- [LoRA Epoch Analyser](https://github.com/Raxephion/loRA-Epoch-Analyser)  
+- [TensorPeek](https://github.com/Raxephion/The-Vault/tree/main/TensorPeek) — for inspecting `.safetensors` metadata  
+- [LoRA Distiller (WIP)](https://github.com/Raxephion/The-Vault) — experimental, but useful in this pipeline
+
+The base model was once again `v1-5-pruned-emaonly.safetensors`, but augmented via LoRA distillation and pre-conditioning to mitigate its quirks. All improvements are checkpoint-native — no merging required.
+
+---
+
+## 🖼️ Sample Images
+
+All images were generated using the base Typhoon V2 checkpoint. No LoRAs, no inpainting, no face fixers — just raw inference with Hires Fix.
+
+**Settings:**
+
+- **Resolution**: 512×768, 576×832, or 640×896  
+- **Sampler**: DPM++ 2M Karras (Euler A also works fine)  
+- **CFG**: 6.5–7  
+- **Hires Fix**:  
+  - Denoising strength: 0.6–0.7  
+  - Upscaler: Latent  
+  - Upscale by: 2  
+- **VAE**: [sd-vae-ft-ema](https://huggingface.co/stabilityai/sd-vae-ft-ema)
+
+⚠️ Legacy `.vae.pt` or `.vae.bin` files will likely cause washed-out or low-contrast results. Use the official VAE or none at all for correct output.
+
+---
+
+## ⚙️ Prompting Tips
+
+- **Trigger Words**: None  
+- **Prompting Style**: Tag-based preferred (e.g. `1girl, long hair, looking at viewer`)  
+- **Natural Language**: Still not a fan — use structured tags for best results  
+- **ADetailer / Face Fixing**: Rarely needed; faces are stable out of the box  
+- **Recommended Resolutions**:  
+  - 512×768  
+  - 576×832  
+  - 640×896  
+  Narrow resolutions like 512×640 are prone to artifacts. Avoid if possible.
+
+---
+
+## ⚠️ Limitations
+
+- **NSFW**: Still mildly neutered by the base model. Performance has improved over V1, but results are hit-or-miss.  
+- **Anatomy**: Much better than V1, but still SD1.5 — expect occasional hiccups  
+- **Natural Language Prompts**: Works better than V1, but short, tag-like prompts still yield the most consistent results
+
+---
+
+## 🔒 License & Usage
+
+- ✅ Personal use: Absolutely  
+- 🚫 **Do NOT** upload this model to generation websites or aggregators  
+- 🚫 **Do NOT** merge this model into other checkpoints  
+
+> Why? Typhoon V2 was trained cleanly and directly. Merging would break its stylistic balance, ruin its improvements, and waste the training effort. Please don’t.
+
+---
+
+## 🔮 Future Work
+
+- Further refinements possible via targeted LoRAs or partial retrains  
+- Potential distillation into an SDXL variant  
+- Ongoing prompt testing and edge-case analysis
+
+---
+
+**Enjoy the storm — again.** ⛈️