Davids048andClaude Opus 5.5
4117696a4f
- Docs, AGENTS.md files, and skills describe ResolvedGeneratorConfig, resolve_inference_config, typed YAML, and --config plus dotted overrides for training and preprocessing instead of FastVideoArgs and flat flags. - The local tests build resolved configs (or small fakes that expose typed paths) instead of FastVideoArgs; the LoRA extraction scripts build pipelines with from_pretrained(model_path, resolved_config=...). - The mixkit README's NVFP4 snippet uses from_config with engine.quantization.transformer_quant (the from_pretrained keyword it used is rejected). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
FastVideo Gradio Local Demo
This is a Gradio-based web interface for generating videos using the FastVideo framework. The demo allows users to create videos from text prompts with various customization options.
Overview
The demo uses the FastVideo framework to generate videos based on text prompts. It provides a simple web interface built with Gradio that allows users to:
- Enter text prompts to generate videos
- Customize video parameters (dimensions, number of frames, etc.)
- Use negative prompts to guide the generation process
- Set or randomize seeds for reproducibility
Usage
Run the demo with:
python examples/inference/gradio/local/gradio_local_demo.py
This will start a web server at http://0.0.0.0:7860 where you can access the interface.
Model Initialization
This demo initializes a VideoGenerator with the minimum required arguments for inference. Users can seamlessly adjust inference options between generations, including prompts, resolution, video length, without ever needing to reload the model.
Video Generation
The core functionality is in the generate_video function, which:
- Processes user inputs
- Uses the FastVideo VideoGenerator from earlier to run inference (
generator.generate())
Gradio Interface
The interface is built with several components:
- A text input for the prompt
- A video display for the result
- Inference options in a collapsible accordion:
- Height and width sliders
- Number of frames slider
- Guidance scale slider
- Negative prompt options
- Seed controls
Inference Options
- Height/Width: Control the resolution of the generated video
- Number of Frames: Set how many frames to generate
- Guidance Scale: Control how closely the generation follows the prompt
- Negative Prompt: Specify what you don't want to see in the video
- Seed: Control randomness for reproducible results