Instructions to use TheDenk/cogvideox-5b-controlnet-canny-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheDenk/cogvideox-5b-controlnet-canny-v1 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("TheDenk/cogvideox-5b-controlnet-canny-v1") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
File size: 816 Bytes
811f545 b49798a 811f545 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"_class_name": "CogVideoXControlnet",
"_diffusers_version": "0.31.0.dev0",
"activation_fn": "gelu-approximate",
"attention_bias": true,
"attention_head_dim": 64,
"downscale_coef": 8,
"dropout": 0.0,
"flip_sin_to_cos": true,
"freq_shift": 0,
"in_channels": 3,
"max_text_seq_length": 226,
"norm_elementwise_affine": true,
"norm_eps": 1e-05,
"num_attention_heads": 30,
"num_layers": 18,
"out_proj_dim": 3072,
"patch_size": 2,
"sample_frames": 49,
"sample_height": 60,
"sample_width": 90,
"spatial_interpolation_scale": 1.875,
"temporal_compression_ratio": 4,
"temporal_interpolation_scale": 1.0,
"time_embed_dim": 512,
"timestep_activation_fn": "silu",
"use_learned_positional_embeddings": false,
"use_rotary_positional_embeddings": false,
"vae_channels": 16
}
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