TC-Fuse model backbone design — the architecture-agnostic embedding layer (TorchSource → EmbeddedSource via MultiSourceEncoder) and un-embedding layer (EmbeddedBatch → DecodedBatch via MultiSourceDecoder), the swappable encoder interface, candidate backbones to benchmark (Perceiver, cross-attention Transformer, hierarchical windowed attention), and the masked-source-reconstruction self-supervised pre-training task. Use when working in `src/tcfuse/models/`, adding or benchmarking a backbone, or changing the encoder/decoder interface.
설치
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
TC-Fuse model backbone design — the architecture-agnostic embedding layer (TorchSource → EmbeddedSource via MultiSourceEncoder) and un-embedding layer (EmbeddedBatch → DecodedBatch via MultiSourceDecoder), the swappable encoder interface, candidate backbones to benchmark (Perceiver, cross-attention Transformer, hierarchical windowed attention), and the masked-source-reconstruction self-supervised pre-training task. Use when working in `src/tcfuse/models/`, adding or benchmarking a backbone, or changing the encoder/decoder interface.
Content has moved. The full skill documentation is in .agents/architecture.md.
Read that file for the embedding/un-embedding layer contracts, the encoder interface, candidate architectures, and the self-supervised pre-training task.
