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README.md

@@ -1,3 +1,21 @@
+---
+library_name: spandrel
+license: other
+license_name: mixed
+license_link: LICENSE
+tags:
+  - image-super-resolution
+  - super-resolution
+  - upscaling
+  - real-esrgan
+  - hat
+  - swinir
+  - comfyui
+  - ffmpega
+  - video-processing
+pipeline_tag: image-to-image
+---
+
 # AI Upscale Models for FFMPEGA
 
 Pre-trained super-resolution models for use with [ComfyUI-FFMPEGA](https://github.com/AEmotionStudio/ComfyUI-FFMPEGA)'s AI Upscale feature.
@@ -7,20 +25,20 @@ Models are automatically downloaded on first use — no manual setup required.
 ## Models
 
 | File | Architecture | Scale | Size | VRAM | Best For |
-|---|---|---|---|---|---|
+|------|-------------|-------|------|------|----------|
 | `RealESRGAN_x4plus.pth` | RRDBNet (GAN) | 4× | 67 MB | ~2 GB | General real-world photos |
 | `RealESRGAN_x4plus_anime_6B.pth` | RRDBNet (compact) | 4× | 18 MB | ~1 GB | Anime, cartoon, illustration |
-| `Real_HAT_GAN_SRx4.pth` | HAT (GAN) | 4× | 170 MB | ~4 GB | **SOTA** — highest quality |
-| `003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth` | SwinIR-Large | 4× | 142 MB | ~3 GB | Classical SR, clean images |
+| `Real_HAT_GAN_SRx4.pth` | HAT (hybrid attention) | 4× | 170 MB | ~4 GB | SOTA quality, fine detail |
+| `003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth` | SwinIR-Large | 4× | 48 MB | ~3 GB | Clean images, classical SR |
 
 All models output 4× resolution. For 2× output, the upscaler runs at 4× then applies high-quality Lanczos downscaling.
 
 ## Usage in FFMPEGA
 
-1. Set **llm_model** → `none`
-2. Set **no_llm_mode** → `ai_upscale`
-3. Choose **upscale_model** (e.g. `hat_x4` for best quality)
-4. Choose **upscale_scale** (`4` or `2`)
+1. Set `llm_model` → `none`
+2. Set `no_llm_mode` → `ai_upscale`
+3. Choose `upscale_model` (e.g. `hat_x4` for best quality)
+4. Choose `upscale_scale` (`4` or `2`)
 5. Connect an image or video input and run
 
 ## Model Loading