This is a GGUF conversion of Wan14BT2VFusioniXfp16.safetensors by @vrgamedevgirl84.
Modellquelle
Quellenbeschreibung
This is a GGUF conversion of Wan14BT2VFusioniX_fp16_.safetensors by @vrgamedevgirl84.
All quantized versions were created from the base T2V FP16 model using the conversion scripts provided by city96, available at the ComfyUI-GGUF GitHub repository.
Verwandte Ressourcen
1 VerbindungQuellen
1 QuelleVerifiziert 13. Okt.
Modellartefakte
15 ArtefakteWan2.1_T2V_14B_FusionX-F16.gguf
gguf · 26,6 GB · SHA-256 6184581cc2f9…45c7 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q2_K.gguf
gguf · 4,94 GB · SHA-256 512d0be0f754…d4ce · Hugging Face
HerunterladenQuellenauszüge
2 AuszügeThe model files can be used in ComfyUI with the ComfyUI-GGUF custom node. Place the required model(s) in the following folders:
| Type | Name | Location | Download |
|---|---|---|---|
| Main Model | Wan2.1_T2V_14B_FusionX-GGUF | ComfyUI/models/unet | GGUF (this repo) |
| Text Encoder | umt5-xxl-encoder | ComfyUI/models/text_encoders | Safetensors / GGUF |
| VAE | Wan2_1_VAE_bf16 | ComfyUI/models/vae | Safetensors |
All original licenses and restrictions from the base models still apply.
Wan2.1_T2V_14B_FusionX-Q3_K_L.gguf
gguf · 7,25 GB · SHA-256 3ca31f77daeb…45d2 · Hugging Face
Wan2.1_T2V_14B_FusionX-Q3_K_M.gguf
gguf · 6,68 GB · SHA-256 ee79f6acbd33…4a00 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q3_K_S.gguf
gguf · 6,07 GB · SHA-256 88805e516824…ed26 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q4_0.gguf
gguf · 7,97 GB · SHA-256 f0ad8f7396a8…1c04 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q4_1.gguf
gguf · 8,62 GB · SHA-256 6a28c4a217d0…fdab · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q4_K_M.gguf
gguf · 8,99 GB · SHA-256 857038e8cecf…3786 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q4_K_S.gguf
gguf · 8,15 GB · SHA-256 1e18c7d6456b…fdc6 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q5_0.gguf
gguf · 9,60 GB · SHA-256 0cba7a27a5fb…543b · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q5_1.gguf
gguf · 10,3 GB · SHA-256 7c074217e2a2…1099 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q5_K_M.gguf
gguf · 10,0 GB · SHA-256 606e0d0eca52…ab04 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q5_K_S.gguf
gguf · 9,44 GB · SHA-256 93e085a73453…f3c2 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q6_K.gguf
gguf · 11,2 GB · SHA-256 48adc9ceb517…ad22 · Hugging Face
HerunterladenWan2.1_T2V_14B_FusionX-Q8_0.gguf
gguf · 14,3 GB · SHA-256 6d7a98926e5d…0f2c · Hugging Face
Herunterladen--- base_model: - vrgamedevgirl84/Wan14BT2VFusioniX base_model_relation: quantized library_name: gguf quantized_by: lym00 tags: - text-to-video - quantized language: - en license: apache-2.0 --- This is a GGUF conversion of [Wan14BT2VFusioniX_fp16_.safetensors](https://huggingface.co/vrgamedevgirl84/Wan14BT2VFusioniX/blob/main/Wan14BT2VFusioniX_fp16_.safetensors) by [@vrgamedevgirl84](https://huggingface.co/vrgamedevgirl84). All quantized versions were created from the base T2V 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. ## Usage The model files can be used in [ComfyUI](https://github.com/comfyanonymous/ComfyUI/) with the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) custom node. Place the required model(s) in the following folders: | Type | Name | Location | Download | | ------------ | ----------------------------- | ------------------------------ | ---------------- | | Main Model | Wan2.1_T2V_14B_FusionX-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) | [**ComfyUI example workflow**](https://docs.comfy.org/tutorials/video/wan/wan-video#wan2-1-text-to-video-workflow) ### Notes *All original licenses and restrictions from the base models still apply.* ## Reference - For an overview of quantization types, please see the [GGUF quantization types](https://huggingface.co/docs/hub/gguf#quantization-types).
Source context: 5681 downloads · 29 likes · Pipeline text-to-video · Library gguf · Repo QuantStack/Wan2.1_T2V_14B_FusionX-GGUF