Instructions to use finetrainers/CogVideoX-1.5-crush-smol-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use finetrainers/CogVideoX-1.5-crush-smol-v0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("finetrainers/CogVideoX-1.5-crush-smol-v0", dtype=torch.bfloat16, device_map="cuda") prompt = "PIKA_CRUSH A red toy car is being crushed by a large hydraulic press, which is flattening objects as if they were under a hydraulic press." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 407803627fff01b70670add26be4569b37de97a1d7627ef2232a3917d13db2b6
- Size of remote file:
- 281 kB
- SHA256:
- b6c507cc7a076e89ee6effa6a3ab03520d5ecac447999f466b590c841ced3703
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.