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Wan2.2-Custom-Models-GGUF

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geceff commited on Jul 4

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@@ -22,7 +22,7 @@ This repository provides highly optimized **Wan2.2 Image-to-Video (I2V) GGUF** a
 ## ⚠️ CRITICAL NOTICE: UN-UPDATED BASE MODEL WARNING
 *   🚨 **Full-Size Base Models:** Please note that the full-size raw models and non-quantized base files **have NOT been updated yet** in this repository.
-*   💡 **Current Availability:** Only the custom-compiled quants (GGUF), specialized LoRAs, Text Encoders (`umt5_xxl_fp16`), VAEs (`Wan2_1_VAE_fp32` / `wan_2.1_bf16`), and specific FP8 integrated models are fully active and optimized for deployment. If you require raw unquantized BF16 weights, please wait for future repository syncs or utilize the available GGUF variants.
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@@ -36,7 +36,7 @@ To achieve perfect video motion without artifacts or image degradation (preventi
 | **CFG Scale** | `1.0 - 2.5` | Crucial for preventing burnt images |
 | **High Noise Steps** | `2`, `4`, `6`, or `8` | To lock in strong motion. Can be split evenly (e.g., 8 steps total = 4 High / 4 Low) |
 | **Low Noise Steps** | *Dynamic* (End Step: `4 - 12`) | **CRITICAL:** The target End Step for Low Noise must **NEVER** exceed the Total Sampling Steps! |
-| **Sampler / Scheduler** | `euler` + `simple` | Standard diffusion setup |
 ### 👑 Note for Higher Quality (Hybrid Workflow & Hardware Restrictions):
 If you want to achieve higher visual fidelity and enhance micro-details, adopting a hybrid multi-pass approach is highly recommended. This strategy significantly sharpens fine details, effectively eliminates motion blur, and prevents fried visuals.

 ## ⚠️ CRITICAL NOTICE: UN-UPDATED BASE MODEL WARNING
 *   🚨 **Full-Size Base Models:** Please note that the full-size raw models and non-quantized base files **have NOT been updated yet** in this repository.
+*   💡 **Current Availability:** Only the custom-compiled quants (GGUF), specialized LoRAs, Text Encoders (`umt5_xxl_fp16 - umt5_xxl_fp8_e4m3fn_scaled`), VAEs (`Wan2_1_VAE_fp32` / `wan_2.1_bf16`), and specific FP8 integrated models are fully active and optimized for deployment. If you require raw unquantized BF16 weights, please wait for future repository syncs or utilize the available GGUF variants.
 ---
 | **CFG Scale** | `1.0 - 2.5` | Crucial for preventing burnt images |
 | **High Noise Steps** | `2`, `4`, `6`, or `8` | To lock in strong motion. Can be split evenly (e.g., 8 steps total = 4 High / 4 Low) |
 | **Low Noise Steps** | *Dynamic* (End Step: `4 - 12`) | **CRITICAL:** The target End Step for Low Noise must **NEVER** exceed the Total Sampling Steps! |
+| **Sampler / Scheduler** | `euler` + `simple` | Standard diffusion setup (Optionally, `uni_pc` can also be used for alternative fast-stepping) |
 ### 👑 Note for Higher Quality (Hybrid Workflow & Hardware Restrictions):
 If you want to achieve higher visual fidelity and enhance micro-details, adopting a hybrid multi-pass approach is highly recommended. This strategy significantly sharpens fine details, effectively eliminates motion blur, and prevents fried visuals.