Files
hao-ai-lab-FastVideo/docs
Davids048andClaude Opus 5.5 c7c2d77fae [bugfix]: apply the LTX-2 refine LoRA to the refine transformer
The from_pretrained keyword ltx2_refine_lora_path set
pipeline.components.lora_path, which reaches FastVideoArgs.lora_path and loads
as the main LoRA on the stage-1 transformer. The refine stage reads
FastVideoArgs.ltx2_refine_lora_path, which stayed unset. The conversion also
turned an empty string into None. An empty string is how callers such as the
Dreamverse GPU pool disable the refine LoRA, and None makes LTX2Pipeline load
the checkpoint default instead: fastvideo_refine_lora_path in model_index.json
is FastVideo/LTX2-Distilled-LoRA for the LTX-2 Diffusers checkpoints.

The refine LoRA gets its own field, pipeline.ltx2.refine.lora_path, whose
flat name is ltx2_refine_lora_path. None keeps the checkpoint default, and an
empty string disables the refine LoRA. The Dreamverse contract test, the
Dynamo contract example, and the parity inventory point at the field.

Golden changes: kwargs/ltx2_refine_lora_path now records the path on
ltx2_refine_lora_path instead of lora_path, and the added case
kwargs/ltx2_refine_lora_disabled pins the empty string.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
2026-10-02 18:29:37 +00:00
..
2026-07-19 18:37:47 -07:00

FastVideo Documentation

This directory contains the FastVideo documentation built with MkDocs.

Build the docs locally

# Install dependencies
uv pip install -r requirements-mkdocs.txt

# Serve docs with live reload (recommended for development)
mkdocs serve

# Or build static site
mkdocs build

View the docs

Development server (with live reload)

mkdocs serve

Then open your browser to: http://127.0.0.1:8000

Static build

mkdocs build
python -m http.server -d site/

Then open your browser to: http://localhost:8000

Automatic Deployment

Documentation is automatically built and deployed to GitHub Pages when changes are pushed to the main branch via the .github/workflows/infra-docs.yml workflow.

Update documentation dependencies

Edit requirements-mkdocs.in, then regenerate the pinned Linux/Python 3.12 lock file:

uv pip compile requirements-mkdocs.in \
  -o requirements-mkdocs.txt \
  --python-platform x86_64-manylinux_2_28 \
  --python-version 3.12