Principle:Zai org CogVideo T2V Pipeline Loading
Overview
Technique for loading a complete text-to-video diffusion pipeline from pretrained weights into a single unified interface.
Description
Pipeline loading instantiates all sub-components (tokenizer, text encoder, transformer denoiser, VAE, scheduler) from a pretrained checkpoint directory and composes them into a single callable object. This encapsulates the full generation workflow (encode text, denoise latents, decode video) behind a simple API. For CogVideoX, the pipeline supports multiple model variants (2B, 5B, 1.5-5B) with automatic resolution selection.
The loading process performs the following steps:
- Tokenizer initialization -- Loads the T5 tokenizer for text preprocessing
- Text encoder loading -- Loads the T5-XXL text encoder for producing text embeddings
- Transformer loading -- Loads the CogVideoX 3D transformer model for denoising
- VAE loading -- Loads the CogVideoX VAE for encoding/decoding between pixel and latent space
- Scheduler configuration -- Initializes the default noise scheduler with pretrained config
All components are loaded in the specified data type (typically bfloat16 for 5B models) and composed into a single CogVideoXPipeline object.
Usage
Use at the start of any text-to-video inference workflow. Choose model variant based on quality/speed tradeoff:
| Model Variant | Resolution | Use Case |
|---|---|---|
| THUDM/CogVideoX-2b | 480 x 720 | Faster inference, lower VRAM |
| THUDM/CogVideoX-5b | 480 x 720 | Higher quality, moderate VRAM |
| THUDM/CogVideoX1.5-5B | 768 x 1360 | Highest quality, highest VRAM |
Theoretical Basis
Diffusion pipelines compose multiple learned components into a single generation workflow:
- text_encoder(prompt) produces conditioning embeddings
- scheduler(timesteps) defines the noise schedule for denoising
- transformer(noisy_latents, conditioning, t) predicts the denoised latents at each timestep
- VAE.decode(latents) maps final denoised latents to pixel-space video frames
The pipeline abstraction hides this multi-step process behind a single callable interface, handling data flow between components, dtype management, and device placement automatically.