Cosmos-Embed

Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery).

Cosmos-Embed1 is a joint video-text embedder for text-to-video retrieval, video-to-video search, zero-shot/kNN classification, and semantic deduplication. The packaged CLI is cosmos-embed1 and supports train, evaluate, inference, and export.

Container image and per-action commands are in references/skill_info.yaml. Compact starting specs are in references/spec_template_*.yaml; the LoRA fine-tuning recipe on chunk manifests is in references/lora-finetune-physicalai.md with references/spec_template_train_lora.yaml.

Release note: the pinned 7.3.0-cosmos-embed image is the first that trains ViT LoRA adapters, accepts caption_mode, label_mode, and train.grad_accum_iter, scores the in-training retrieval_benchmark, and validates large ONNX exports by file path. On 7.1.0-cosmos-embed the ViT adapters silently stay at zero and the vision ONNX export exits 1 after writing valid files.

Train Action Policy

AutoML is not packaged for this model skill (no Cosmos-Embed schemas under schemas/). Use the direct train, evaluate, inference, and export actions even when a higher-level request includes automl_policy: on; the per-run override does not change model metadata, and non-train and deploy flows stay in this skill.

Quick Start

Use the published container pinned below (also declared in references/skill_info.yaml); do not build from the Cosmos-Embed1 source tree for normal skill use.