Text-to-Video
Diffusers
Diffusion Single File
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t2v
video generation
comfyui
distillation
LoRA
Instructions to use lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
I tried to reproduce i2v-14b-bi self-forcing-plus training but encountered problems, can you help me? Thanks!
#14
by lj1995 - opened
"I2V-480P Training
DataSet Preparation
Generate a series of videos using the original Wan2.1 model."
I used I2V-14B-480P-step_cfg_distilled model to generate about 3w videos. 8steps+cfg1.
The trained distilled i2v-14b-bi model (training is followed by "I2V-480P Training" readme) inferenced noise videos.
1、Should I use T2V-14B model to generate the videos as the training set?
2、Can I use your distilled T2V-14B model for faster inference as the training set?
3、Can I use the real world videos as the training set?