Update README.md

README.md

@@ -1,6 +1,6 @@
 ---
 base_model:
-- QuantStack/Wan2.1-14B-T2V-FusionX-VACE
+- QuantStack/Wan2.1_T2V_14B_FusionX_VACE
 base_model_relation: quantized
 library_name: gguf
 quantized_by: lym00
@@ -14,7 +14,7 @@ language:
 license: apache-2.0
 ---
 
-This is a GGUF conversion of [QuantStack/Wan2.1-14B-T2V-FusionX-VACE](https://huggingface.co/QuantStack/Wan2.1-14B-T2V-FusionX-VACE).
+This is a GGUF conversion of [QuantStack/Wan2.1_T2V_14B_FusionX_VACE](https://huggingface.co/QuantStack/Wan2.1_T2V_14B_FusionX_VACE).
 
 All quantized versions were created from the base FP16 model using the conversion scripts provided by city96, available at the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF/tree/main/tools) GitHub repository. 
 
@@ -24,7 +24,7 @@ The model files can be used in [ComfyUI](https://github.com/comfyanonymous/Comfy
 
 | Type         | Name                             | Location                       | Download         |
 | ------------ | -------------------------------- | ------------------------------ | ---------------- |
-| Main Model   | Wan2.1-14B-T2V-FusionX-VACE-GGUF | `ComfyUI/models/unet`          | GGUF (this repo) |
+| Main Model   | Wan2.1_T2V_14B_FusionX_VACE-GGUF | `ComfyUI/models/unet`          | GGUF (this repo) |
 | Text Encoder | umt5-xxl-encoder                 | `ComfyUI/models/text_encoders` | [Safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/text_encoders) / [GGUF](https://huggingface.co/city96/umt5-xxl-encoder-gguf/tree/main) |
 | VAE          | Wan2_1_VAE_bf16                  | `ComfyUI/models/vae`           | [Safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1_VAE_bf16.safetensors) |
 
@@ -36,5 +36,4 @@ The model files can be used in [ComfyUI](https://github.com/comfyanonymous/Comfy
 
  ## Reference
 
-- For more information about the source model, refer to [QuantStack/Wan2.1-14B-T2V-FusionX-VACE](https://huggingface.co/QuantStack/Wan2.1-14B-T2V-FusionX-VACE), where the model creation process is explained.
 - For an overview of quantization types, please see the [GGUF quantization types](https://huggingface.co/docs/hub/gguf#quantization-types).