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@@ -11,17 +11,4 @@ Inference code is available here: [github.com/jy0205/Pyramid-Flow](https://githu
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  Both 384p and 768p work on 24 GB VRAM. For 16 steps (5 second video), 384p takes a little over a minute on a 3090, and 768p takes about 7 minutes. For 31 steps (10 second video), 384p took about 10 minutes.
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- In `diffusion_schedulers/scheduling_flow_matching.py`, in the function `init_sigmas_for_each_stage`, one small change needs to be made:
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- Change this line:
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- ```
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- self.timesteps_per_stage[i_s] = torch.from_numpy(timesteps[:-1])
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- ```
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- To this:
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- ```
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- self.timesteps_per_stage[i_s] = timesteps[:-1]
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- ```
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-
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- This will allow the model to be compatible with newer versions of pytorch and other libraries than is shown in the requirements.
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- Working with torch2.4.1+cu124.
 
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  Both 384p and 768p work on 24 GB VRAM. For 16 steps (5 second video), 384p takes a little over a minute on a 3090, and 768p takes about 7 minutes. For 31 steps (10 second video), 384p took about 10 minutes.
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+ I highly recommend using `cpu_offloading=True` when generating, unless you have more than 24 GB VRAM.