118 lines
7.3 KiB
Markdown
118 lines
7.3 KiB
Markdown
# Documentation and cookbook plan
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Readers should be able to choose a model, find their hardware path, generate a
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result, and then customize or train it without searching several sections for
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the same instructions.
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## One home for each kind of information
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| Area | Question it answers | Owns |
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| --------------------- | ---------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
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| Fast Models | Which FastVideo release should I choose? | Our released families, checkpoint exports, collections, short capability descriptions, links to recipes |
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| Support matrix | What else can FastVideo run? | The wider supported model set and optimization compatibility |
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| Hardware and runtimes | Where can I run it? | NVIDIA RTX/workstation and data center CUDA paths, DGX Spark, Apple MLX, AMD ROCm, platform requirements and limits |
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| Documentation | How does FastVideo work? | Installation, the first generation, configuration, CLI, parallelism, offloading, integrations, training, architecture and API reference |
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| Cookbook | How do I run this model for this task? | One family home, runtime choices, runnable recipes, model-specific configuration, troubleshooting and evidence |
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Fast Models highlights our models without implying that FastVideo only supports
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those releases. CUDA and ROCm are runtimes; RTX, data center GPUs and DGX Spark
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are hardware paths. MLX is the Apple Silicon runtime. These distinctions should
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be visible before readers choose an installation command.
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## Included now
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- One Hardware and runtimes overview links the five hardware paths. AMD is
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explicitly source-backed support with incomplete installation/device coverage,
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rather than a promise that CUDA recipes or kernels work on every AMD GPU.
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- The getting-started sidebar contains Quick start, Installation, Hardware and
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runtimes, and Python API basics.
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- Run inference contains shared tasks. Hardware and Integrations are expandable
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groups; individual hardware recipes do not interrupt onboarding.
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- Model-specific references sit beside their family recipes in the Cookbook
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sidebar. There is no separate Model guides list competing with the cookbook.
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Existing LTX, Kandinsky and FastH3 reference URLs remain intact.
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- Fast Models points FastH3 and FastWan readers to their cookbook families.
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FastMetal also has a direct MLX setup entry.
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- Generated examples have one visible page title, with the source link below it.
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Their previous heading fragments remain available.
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## The intended reader flow
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1. Start at **Fast Models** to choose a released model, or the support matrix for
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the broader catalog.
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2. Check **Hardware and runtimes**, then follow the matching installation guide.
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3. Open the model's **Cookbook family**. Choose the task and runtime, configure
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a recipe, and run it.
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4. Follow links to shared configuration, offloading or optimization docs when
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more explanation is needed.
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5. Move to training, distillation or contributor guides for development work.
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The quick start remains a short route for readers who want a first result before
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browsing the catalog.
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## Next editorial pass
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1. **Consolidate onboarding.** Keep one first-video tutorial. Remove repeated
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installation blocks from the inference quick start after preserving its unique
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image-conditioning examples. Make Installation a platform chooser and keep
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installation commands in platform guides.
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2. **Give every model one family home.** Expand the cookbook family page with a
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short capability overview, runtime/task recipes, checkpoint choices, limits,
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troubleshooting and next steps. Fold overlapping model-specific guides into
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that page or link a detailed reference from it. Preserve old routes with
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redirects before deleting any page.
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3. **Separate explanation from recipes.** Hardware owns environment setup;
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cookbook owns model commands; shared docs explain the options. The RTX PRO
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6000 page's kernel internals and rejected experiments belong in research or
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contributor material, separate from its runnable recipe.
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4. **Reduce pointer pages and duplicate references.** Replace the two-sentence
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ComfyUI pointer with a useful integration guide, or link directly to its
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maintained README. Reconcile the two attention-backend development guides.
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Let Architecture own the package map instead of repeating it in the agent guide.
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5. **Split long optimization material by task.** Keep attention selection,
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quantization, distributed execution and offloading cross-linked, with one
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owner for each setting. Keep STA and mask search clearly archived.
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6. **Fill the ROCm evidence gap.** Document a complete AMD installation and model
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run with GPU architecture, ROCm/PyTorch versions, model revision, attention
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backend, expected output and measured memory. Source implementation alone
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should not turn into a broad device-support claim.
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## Per-page structure
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Task guides follow: outcome → requirements → runnable example → expected output
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→ configuration → troubleshooting → next step. A model recipe adds its checkpoint,
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workload, runtime, hardware evidence and measured limitations. Detailed reference
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and implementation history should not interrupt setup commands.
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See the [authoring guide](../docs/contributing/documentation.md). Examples and
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Python reference stay source-generated and searchable; they do not need hundreds
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of sidebar entries.
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## Publishing
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Blume replaces MkDocs through the existing GitHub Pages workflow at
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`https://haoailab.com/FastVideo/`. Only `main` deploys. The migration manifest
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checks previous routes and heading fragments. This PR changes navigation and
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presentation while keeping the technical content available; the consolidation
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steps above remain editorial follow-ups.
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## Cookbook model pages
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The cookbook catalog includes the maintained video, image, audio, and world
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models, with category and family filters. FastH3 appears first. Each checkpoint
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has its own page; related task or hardware recipes become variants on that page.
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Family groups hold the pages alongside their broader runbooks.
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FastH3 8-Step V2, FastWan2.1 1.3B, Wan2.1 I2V 14B, and LTX2 Distilled use the five
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existing editable serving deployments. Their pages have a model header, YAML
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actions, generated commands, and a compact hardware/options matrix. Other models
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publish existing source commands and YAML without inventing editable settings.
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Hardware-fit validation remains unverified. New quantization, encoder, or runtime
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choices require a backend recipe before becoming selectable.
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The retired page-copy and tab handlers, cookbook JavaScript, and theme styles are
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removed. Canonical callouts now use Blume syntax, so builds no longer execute a
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migration codemod. Existing family URLs show React model cards with their setup
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and troubleshooting content. The homepage adds a direct FastH3 recipe link while
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keeping the existing logo, news, project cards, typography, and backgrounds.
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