Results for “invariants”
12 skillsMore results
machenjie Unit Testing
`analysis-agent`/`task-agent`/`review-agent`: use when logic, rules, invariants, branches, edges, or failure paths need isolated tests; skip without a unit-test decision.
4 · bundle
machenjie Domain Impact Modeler
Use `analysis-agent` to identify domain ownership, invariants, state transitions, and cross-context effects when rules change or ownership is unclear. Skip presentation-only or question-only work with no domain behavior.
4 · bundle
nvidia Tao Train Nvdinov2
Trains vision transformers via self-distillation without labels for self-supervised visual representation learning, and supports export and inference of NVDINOv2 backbones.
2.2k · bundle
mukul975 Assessing Vector And Embedding Weaknesses
Test vector stores for embedding inversion, cross-tenant leakage, and poisoning.
24.6k · bundle
jiachen-t-wang Snli Ve Visual Entailment Dataset Arxiv 1901 06706v1
SNLI-VE: Visual Entailment Dataset
6
machenjie Transaction Consistency
Use with analysis-agent or task-agent for task-local transaction, isolation, and conflict decisions. Do not use without a transaction decision or as task owner.
4 · bundle
jiachen-t-wang Flamingo A Visual Language Model For Few Shot Learning Arxiv
Flamingo: A Visual Language Model for Few-Shot Learning
6
qcmuu Mamba Architecture
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
0 · bundle
tianhao909 Mamba Architecture
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
1 · bundle
affaan-m Iterative Retrieval
Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.
226k
seaworld008 Dawn
Proposes exactly one personal side-project idea per invocation, sized to a 1-3 day MVP. Targets CLI, automation, LLM, DX, productivity, and data-viz angles; avoids clichés like TODO apps, weather apps, and pomodoro timers. Output is an 8-section brief including a ready-to-paste coding-agent prompt. Use for morning/daily idea rituals and weekend-hack ideation. Don't use for existing-product feature proposals (Spark), dialogue brainstorming (Riff), or prototype implementation (Forge).
65