Co-authored-by: Will Lin <willlin@nvidia.com> Co-authored-by: William Lin <8941107+SolitaryThinker@users.noreply.github.com> Co-authored-by: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
2.0 KiB
2.0 KiB
FastVideo CLI Inference
The FastVideo CLI is config-first. Inference runs are driven by a nested JSON or
YAML config, with optional dotted-path overrides on the command line. The
contract matches training: use an explicit subcommand plus --config, then add
any dotted overrides you need.
Basic Usage
fastvideo generate --config config.yaml
fastvideo serve --config serve.yaml
View All Arguments
fastvideo generate --help
The subcommands intentionally expose only --config. Any per-run CLI changes
must use dotted override paths such as:
--generator.engine.num_gpus 2--request.sampling.seed 42--server.port 9000
Using Config Files
fastvideo generate --config config.yaml
Config files can be JSON or YAML. Dotted CLI overrides take precedence over config-file values.
Example config.yaml:
generator:
model_path: FastVideo/FastHunyuan-diffusers
engine:
num_gpus: 2
parallelism:
sp_size: 2
tp_size: 1
request:
prompt: A capybara lounging in a hammock
sampling:
num_frames: 45
height: 720
width: 1280
num_inference_steps: 6
seed: 1024
output:
output_path: outputs/
Notes:
generatorandrequestare the top-level keys for generation configs.serveconfigs usegenerator,server, and optionaldefault_request.- Prompt text files belong under
request.inputs.prompt_path. - Launcher-owned multi-node jobs set
generator.engine.execution_backend: external_launcherin this same nested config. This backend is offline-only and is rejected byfastvideo serve; see Distributed Inference fortorchrunand nativesruncommands.
Examples
Simple generation:
fastvideo generate --config config.yaml
Config + dotted override:
fastvideo generate --config config.yaml --request.prompt "A panda skiing at sunset"
Helper wrapper with positional config path:
bash scripts/inference/run.sh scripts/inference/inference_wan.yaml