structcast-model

Name: structcast-model
Availability: InStock
Author: f6ra07nk14

Generate PyTorch, Flax, and Keras models from YAML templates.

Updated Feb 13, 2026

Search Tags:#PyTorch #YAML #model generation #Keras #Flax

Ready to run

npx skills add https://github.com/f6ra07nk14/structcast-model --skill structcast-model

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: structcast-model
Source: https://github.com/f6ra07nk14/structcast-model/tree/main
Command: npx skills add https://github.com/f6ra07nk14/structcast-model --skill structcast-model

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires torch, flax, keras, structcast, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the process of generating PyTorch, Flax, and Keras models from YAML templates, enabling users to create and train models declaratively without writing extensive code.

Core Features & Use Cases

Model Generation: Generate PyTorch, Flax, and Keras models from YAML templates.
Training Workflow: Generate PyTorch training workflows and CLI commands.
Configuration: Describe model architecture, optimizer logic, dataset configuration, and training orchestration declaratively in YAML templates.
Use Case: If you need to create a new ConvNeXtV2 model for PyTorch, you can use this Skill to generate the necessary model code from a YAML template.

Quick Start

Run the following command to generate a PyTorch model from a YAML template:

scm torch create model cfg/torch/models/ConvNeXtV2.yaml

Frequently Asked Questions about structcast-model

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate PyTorch, Flax, or Keras models from a YAML template?▼

You can generate PyTorch, Flax, and Keras models from YAML templates by defining architecture, optimizer, and dataset configurations declaratively. This automates code generation, allowing you to create models without writing extensive boilerplate code.

Can I define model training workflows and optimizer logic declaratively in YAML?▼

Yes, you can describe model architecture, optimizer logic, dataset configuration, and training orchestration declaratively in YAML templates. The Skill processes these templates to generate the corresponding training workflows and CLI commands.

What do I need to run YAML configurations to create machine learning models?▼

You need Python installed along with the appropriate frameworks and libraries, specifically PyTorch, Flax, and Keras. These dependencies are required to execute the YAML configurations and generate the functional model code.

Is there a quick way to create a ConvNeXtV2 model for PyTorch?▼

Yes, you can generate a ConvNeXtV2 model for PyTorch by running a CLI command that points to your YAML template, such as 'scm torch create model cfg/torch/models/ConvNeXtV2.yaml', which generates the necessary model code automatically.

What is the best way to automate machine learning model prototyping across multiple frameworks?▼

Automating model prototyping across multiple frameworks is best achieved by using declarative YAML templates to generate PyTorch, Flax, and Keras models. This approach eliminates extensive manual coding and standardizes architecture definitions.