Per the RAM comment, you may able to get it run locally with two tweaks:

1) Free up the t5 as soon as the text is encoded, so you reclaim GPU RAM

2) Manual Layer Offloading; move layers off GPU once they're done being used to free up space for the remaining layers + activations

Any idea on the minimum VRAM footprint with those tweaks? 20GB seems high for a 2B model. I guess the T5 encoder is responsible for that.

	▲	schopra909 an hour ago \| parent [-]
		T5 Encoder is ~5B parameters so back of the envelope would be ~10GB of VRAM (it's in bfloat16). So, for 360p should take ~15 GB RAM (+/- a few GB based on the duration of video generated). We can update the code over the next day or two to provide the option for delete VAE after the text encoding is computed (to save on RAM). And then report back the GB consumed for 360p, 720p 2-5 seconds on GitHub so there are more accurate numbers. Beyond the 10 GB from the T5, there's just a lot of VRAM taken up by the context window of 720p video (even though the model itself is 2B parameters).