better example code.

This commit is contained in:
sayakpaul
2024-11-29 13:07:26 +05:30
parent 4e3bb7ab5f
commit e1866d844d
+21 -1
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@@ -102,7 +102,27 @@ The model was trained using [CogVideoX Factory](https://github.com/a-r-r-o-w/cog
Requires the [🧨 Diffusers library](https://github.com/huggingface/diffusers) installed.
```py
TODO
from diffusers import MochiPipeline
from diffusers.utils import export_to_video
import torch
pipe = MochiPipeline.from_pretrained("genmo/mochi-1-preview")
pipe.load_lora_weights("CHANGE_ME")
pipe.enable_model_cpu_offload()
pipeline_args = {
"prompt": "CHANGE_ME",
"guidance_scale": 6.0,
"num_inference_steps": 64,
"height": 480,
"width": 848,
"max_sequence_length": 256,
"output_type": "np",
}
with torch.autocast("cuda", torch.bfloat16)
video = pipe(**pipeline_args).frames[0]
export_to_video(video)
```
For more details, including weighting, merging and fusing LoRAs, check the [documentation](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) on loading LoRAs in diffusers.