Merge fea47e70f7 into ec902046f6

This fixes an edge case in the FlowUniPCMultistepScheduler where using high sampling step counts (> 50) would cause an assertion error in the last step. The issue was that with lower_order_final=True, the order calculation could become 0 when step_index equals len(timesteps), causing 'assert self.this_order > 0' to fail.

The fix ensures this_order is always at least 1, maintaining stability while allowing higher quality generation with increased step counts.

🤖 Generated with Claude Code
Co-Authored-By: Claude noreply@anthropic.com

README.md

@@ -36,7 +36,7 @@ In this repository, we present **Wan2.1**, a comprehensive and open suite of vid
 
 ## Community Works
 If your work has improved **Wan2.1** and you would like more people to see it, please inform us.
-- [Phantom](https://github.com/Phantom-video/Phantom) has developed a unified video generation framework for single and multi-subject references based on **Wan2.1-T2V-1.3B**. Please refer to [their examples](https://github.com/Phantom-video/Phantom).
+- [Phantom](https://github.com/Phantom-video/Phantom) has developed a unified video generation framework for single and multi-subject references based on both **Wan2.1-T2V-1.3B** and **Wan2.1-T2V-14B**. Please refer to [their examples](https://github.com/Phantom-video/Phantom).
 - [UniAnimate-DiT](https://github.com/ali-vilab/UniAnimate-DiT), based on **Wan2.1-14B-I2V**, has trained a Human image animation model and has open-sourced the inference and training code. Feel free to enjoy it!
 - [CFG-Zero](https://github.com/WeichenFan/CFG-Zero-star) enhances **Wan2.1** (covering both T2V and I2V models) from the perspective of CFG.
 - [TeaCache](https://github.com/ali-vilab/TeaCache) now supports **Wan2.1** acceleration, capable of increasing speed by approximately 2x. Feel free to give it a try!

wan/utils/fm_solvers_unipc.py

@@ -712,9 +712,9 @@ class FlowUniPCMultistepScheduler(SchedulerMixin, ConfigMixin):
         self.timestep_list[-1] = timestep  # pyright: ignore
 
         if self.config.lower_order_final:
-            this_order = min(self.config.solver_order,
+            this_order = max(1, min(self.config.solver_order,
                              len(self.timesteps) -
-                             self.step_index)  # pyright: ignore
+                             self.step_index)) # pyright: ignore
         else:
             this_order = self.config.solver_order