Design model registries for AI versioning. TRIGGERS - Use when user needs help with ai-model-registry related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Design model registries for AI versioning. TRIGGERS - Use when user needs help with ai-model-registry related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Design model registries for AI versioning. TRIGGERS - Use when user needs help with ai-model-registry related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
日本語の概要は準備中です。原文の説明を表示しています。
Establish model registry standards, governance controls, metadata schemas, approvals, and lifecycle policies for enterprise AI deployments.
日本語の概要は準備中です。原文の説明を表示しています。
Curated download URLs and target directories, organized by family (Flux, WAN, LTX, Qwen, Z-Image, SD15/SDXL), for every model the comfyui-mcp skills reference, covering checkpoints, VAEs, text encoders, and LoRAs. Use when downloading models with download_model (action:"download" / action:"download_civitai"), when a workflow fails with a missing-model error, or when setting up a new machine.
日本語の概要は準備中です。原文の説明を表示しています。
Guide for maintaining the MassGen model and backend registry. This skill should be used when adding new models, updating model information (release dates, pricing, context windows), or ensuring the registry stays current with provider releases. Covers both the capabilities registry and the pricing/token manager.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guidance for Comet ML, the platform for tracking machine learning experiments, managing models, and monitoring production ML systems. Helps developers log experiments, compare model versions, and build reproducible ML pipelines with automatic code/data versioning.
日本語の概要は準備中です。原文の説明を表示しています。
Register trained models in MLflow Model Registry with version control, implement stage transitions (Staging, Production, Archived) with approval workflows, and manage model lineage with comprehensive metadata and deployment tracking. Use when promoting a trained model from experimentation to production, managing multiple model versions across development stages, implementing approval workflows for governance, rolling back to previous versions, or auditing model changes for compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
日本語の概要は準備中です。原文の説明を表示しています。