Instructions to use LanguageBind/Open-Sora-Plan-v1.3.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LanguageBind/Open-Sora-Plan-v1.3.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LanguageBind/Open-Sora-Plan-v1.3.0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "WFVAEModel", | |
| "_diffusers_version": "0.28.0", | |
| "base_channels": 128, | |
| "decoder_energy_flow_hidden_size": 128, | |
| "decoder_num_resblocks": 2, | |
| "dropout": 0.0, | |
| "encoder_energy_flow_hidden_size": 64, | |
| "encoder_num_resblocks": 2, | |
| "latent_dim": 8, | |
| "use_attention": true, | |
| "norm_type": "layernorm", | |
| "t_interpolation": "trilinear", | |
| "connect_res_layer_num": 2 | |
| } | |