# What Pre-Trained Models Are Available for Text-to-CAD? > Explore twelve pre-trained text-to-CAD models including Formula-1 cars and robots. Instantly render 3D designs with the earthtojake/text-to-cad repository's CLI or Python API. No extra training needed. - Repository: [earthtojake/text-to-cad](https://github.com/earthtojake/text-to-cad) - Tags: deep-dive - Published: 2026-09-13 --- **The earthtojake/text-to-cad repository ships with twelve ready-to-use CAD definitions—including Formula-1 cars, humanoid robots, and mechanical assemblies—that you can render instantly via the `cadgen` skill CLI or Python API without additional training or data collection.** The `text-to-cad` project provides a complete pipeline for converting natural language into manufacturable CAD files. At its core, the `cadgen` package (located in `packages/cadgen/`) includes a curated library of pre-trained model definitions stored under the top-level `models/` directory. These definitions contain complete geometric hierarchies, material specifications, and assembly instructions required to generate STEP and GLB outputs on-the-fly. ## Complete Library of Pre-Trained Text-to-CAD Models The repository organizes models into thematic categories. Each model lives in its own subfolder (e.g., `models/f1/`) and includes a dedicated [`README.md`](https://github.com/earthtojake/text-to-cad/blob/main/README.md) and source directory (`src/`) containing the Python geometry definitions. ### Automotive and Racing Vehicles - **`f1`** — Formula-1 race car featuring a detailed monocoque, suspension geometry, power-unit assembly, and aerodynamic surfaces. - **`f14d`** — F-14D Tomcat fighter jet with configurable wings, nose gear, and main landing gear assemblies. - **`hypercar`** — High-performance hyper-car with advanced chassis architecture, power-train layout, suspension systems, and integrated lighting. - **`w16`** — 16-cylinder automotive engine block complete with crank shaft, pistons, cam drive, oil system, and cooling passages. - **`motorbike`** — Complete motorcycle assembly with frame, wheels, mirrors, seat, and lighting fixtures. ### Robotics and Humanoids - **`juno`** — Full-body humanoid robot including torso, pelvis, upper and lower limbs, and wrist carrier modules. - **`lyra`** — Articulated human hand model with individual finger segments, knuckle joints, and palm geometry. - **`tendon_hand`** — Soft-actuated robotic hand driven by tendon cables; includes an interactive web demo. ### Component Libraries and Assemblies - **`drawings`** — Modular library of generic CAD components such as mounting brackets, plates, and fasteners. - **`assemblies`** — Example multi-part assemblies demonstrating how to combine individual model parts (e.g., a complete robot arm). - **`moonwatch`** — Classic wristwatch model comprising case, dial, strap, and mechanical movement housing. - **`examples`** — Minimal demonstration models used for integration testing and documentation tutorials. ## How to Generate CAD Files from Pre-Trained Models You can invoke these models through three primary interfaces: the command-line tool, the Python `ModelBuilder` class, or the interactive Jupyter viewer. ### Command-Line Generation with `cadgen` The `cadgen` skill CLI provides the fastest path from model name to manufacturable file. Install the package per [`packages/cadgen/README.md`](https://github.com/earthtojake/text-to-cad/blob/main/packages/cadgen/README.md), then use the `model` subcommand. Export a hyper-car as a STEP file for manufacturing: ```bash cadgen model hypercar --output hypercar.step ``` Generate a GLB preview of the F1 car for web viewing: ```bash cadgen model f1 --format glb --output f1.glb ``` ### Programmatic Access via Python For batch processing or integration into larger pipelines, import `ModelBuilder` from the `cadgen` package. The builder resolves model source files automatically from `models//src/`. ```python from cadgen import ModelBuilder # Load motorbike geometry builder = ModelBuilder.from_model('motorbike') # Export manufacturing-ready STEP builder.export_step('motorbike.step') # Export lightweight GLB for web preview builder.export_glb('motorbike.glb') ``` ### Interactive Preview in Jupyter The built-in viewer renders models directly in notebook cells without exporting to disk first. ```python from cadgen.viewer import Viewer viewer = Viewer() viewer.display_model('lyra') # Renders the hand model interactively ``` ## Model Architecture and Source Organization Understanding the file structure helps when extending or debugging a model. Each pre-trained model follows a strict convention: - **`models//README.md`** — Contains model-specific documentation, parameter descriptions, and preview assets. - **`models//src/`** — Houses the Python modules that define the geometry, joints, and material hierarchies. - **[`packages/cadgen/README.md`](https://github.com/earthtojake/text-to-cad/blob/main/packages/cadgen/README.md)** — Documents the core runtime, CLI entry points, and `ModelBuilder` API signatures. The `cadgen` library treats these directories as immutable, versioned assets. When you call `ModelBuilder.from_model('f14d')`, the loader imports the geometry definition from `models/f14d/src/` and caches the compiled boundary representation for subsequent exports. ## Summary - **earthtojake/text-to-cad** provides twelve pre-trained CAD models spanning vehicles, humanoids, and mechanical components. - All models reside in the `models/` directory and are ready to render without training or data collection. - The `cadgen` skill CLI supports direct export to **STEP** (manufacturing) and **GLB** (web/visualization) formats. - Python users can leverage `ModelBuilder.from_model()` and `export_step()`/`export_glb()` for scripted workflows. - Interactive development is supported via `cadgen.viewer.Viewer` for Jupyter environments. ## Frequently Asked Questions ### What file formats can I export from text-to-cad pre-trained models? The `cadgen` tool chain supports **STEP** (ISO 10303) for CNC manufacturing and **GLB** (glTF 2.0) for web and real-time visualization. The CLI exposes these via the `--format` flag, while the Python API offers explicit `export_step()` and `export_glb()` methods on the `ModelBuilder` instance. ### Do I need to train these models before using them? No. The models are **pre-trained** in the sense that they ship with complete geometric definitions and assembly logic. You can run `cadgen model f1` immediately after installation without downloading weights or performing fine-tuning. The term "pre-trained" here refers to the CAD domain expertise encoded in the source files under `models//src/`. ### How do I add a custom model to the cadgen library? Create a new directory under `models/` with a `src/` subfolder containing your Python geometry definitions. You must implement the standard model interface expected by `ModelBuilder` (see `models/examples/src/` for a template). Once the directory contains a valid [`README.md`](https://github.com/earthtojake/text-to-cad/blob/main/README.md) and source modules, the `cadgen model ` command will recognize it automatically. ### Where are the model geometry definitions stored? Each model's Python source code resides in `models//src/`. For example, the Juno humanoid logic is located in `models/juno/src/`. The `ModelBuilder` class dynamically imports these modules at runtime based on the string identifier passed to `from_model()`.