FastVideo CLI Inference¶
The FastVideo CLI exposes the same core inference controls as the Python API.
Basic Usage¶
Use either:
--model-path+--prompt--model-path+--prompt-txt(batch prompts, one line per prompt)--config(JSON/YAML)
fastvideo generate --model-path Wan-AI/Wan2.1-T2V-1.3B-Diffusers \
--prompt "A cat playing with a ball of yarn"
You cannot provide both --prompt and --prompt-txt in the same run.
View All Arguments¶
Arguments come from:
- FastVideo runtime args (
FastVideoArgs) - Sampling args (
SamplingParam) - Pipeline config args (
PipelineConfig)
Common Arguments¶
Parallelism¶
--num-gpus--sp-size--tp-size
Sampling¶
--num-frames--height/--width--num-inference-steps--guidance-scale--seed--negative-prompt
Output¶
--output-path--save-video/--no-save-video--return-frames
Offloading and Performance¶
--dit-layerwise-offload--use-fsdp-inference--text-encoder-cpu-offload--image-encoder-cpu-offload--vae-cpu-offload--enable-torch-compile--torch-compile-kwargs
Using Config Files¶
Config files can be JSON or YAML. CLI flags override config-file values.
Example config.yaml:
model_path: "FastVideo/FastHunyuan-diffusers"
prompt: "A capybara lounging in a hammock"
output_path: "outputs/"
num_gpus: 2
sp_size: 2
tp_size: 1
num_frames: 45
height: 720
width: 1280
num_inference_steps: 6
seed: 1024
dit_precision: "bf16"
vae_precision: "fp16"
vae_tiling: true
vae_sp: true
enable_torch_compile: false
Notes:
- Use
dit_precision/vae_precision(notprecision). - Nested config objects are supported, for example
vae_configanddit_config.
Examples¶
Simple generation:
fastvideo generate \
--model-path FastVideo/FastHunyuan-diffusers \
--prompt "A cat playing with a ball of yarn" \
--num-frames 45 --height 720 --width 1280 \
--num-inference-steps 6 --seed 1024 \
--output-path outputs/
Config + CLI override: