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README.md

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+---
+library_name: diffusers
+tags:
+- fp8
+- safetensors
+- lora
+- low-rank
+- diffusion
+- converted-by-gradio
+---
+
+# FP8 Model with Low-Rank LoRA
+
+- **Source**: `https://huggingface.co/Kijai/WanVideo_comfy`
+- **File**: `Wan2_1_VAE_bf16.safetensors`
+- **FP8 Format**: `E5M2`
+- **LoRA Rank**: 32
+- **LoRA File**: `Wan2_1_VAE_bf16-lora-r32.safetensors`
+
+## Usage (Inference)
+
+```python
+from safetensors.torch import load_file
+import torch
+
+# Load FP8 model
+fp8_state = load_file("Wan2_1_VAE_bf16-fp8-e5m2.safetensors")
+lora_state = load_file("Wan2_1_VAE_bf16-lora-r32.safetensors")
+
+# Reconstruct approximate original weights
+reconstructed = {}
+for key in fp8_state:
+    if f"lora_A.{key}" in lora_state and f"lora_B.{key}" in lora_state:
+        A = lora_state[f"lora_A.{key}"].to(torch.float32)
+        B = lora_state[f"lora_B.{key}"].to(torch.float32)
+        lora_weight = B @ A  # (rank, out) @ (in, rank) -> (out, in)
+        fp8_weight = fp8_state[key].to(torch.float32)
+        reconstructed[key] = fp8_weight + lora_weight
+    else:
+        reconstructed[key] = fp8_state[key].to(torch.float32)
+```
+
+> Requires PyTorch ≥ 2.1 for FP8 support.