Update README.md

README.md

@@ -17,4 +17,37 @@ It is optimized to significantly reduce VRAM usage while maintaining high-qualit
 ## Quantization Tool
 
 This model was quantized using the following open-source tool:
-* **Quantizer**: [comfy-dit-quantizer](https://github.com/bedovyy/comfy-dit-quantizer)
+* **Quantizer**: [comfy-dit-quantizer](https://github.com/bedovyy/comfy-dit-quantizer)
+
+There are two models - FP8 and FP8-balanced
+
+- FP8 (2.4GB) : (***recommend***) maximize generation speed while preserving quality as much as possible.
+- FP8-balanced : (***Personal Preference***) retain the prefix and suffix blocks intact, while exclusively modifying the Self-Attention and MLP layers. As a result, its performance is remarkably close to the original BF16 model.
+
+## Quantized layers
+
+### fp8
+```json
+{
+  "format": "comfy_quant",
+  "block_names": ["net.blocks."],
+  "rules": [
+    { "policy": "keep", "match": ["blocks.0", "blocks.1."] },
+    { "policy": "float8_e4m3fn", "match": ["q_proj", "k_proj", "v_proj", "o_proj", "output_proj", ".mlp"] },
+    { "policy": "nvfp4", "match": [] }
+  ]
+}
+```
+
+### fp8-balanced
+```json
+{
+  "format": "comfy_quant",
+  "block_names": ["net.blocks."],
+  "rules": [
+    { "policy": "keep", "match": ["blocks.0.", "blocks.1.", "blocks.26.", "blocks.27."] },
+    { "policy": "float8_e4m3fn", "match": ["self_attn.", ".mlp"] },
+    { "policy": "nvfp4", "match": [] }
+  ]
+}
+```