ruview-model-training

SKILLWorkflowcommunauté
v0.0.0ruvnetMITMis à jour il y a 5 jSource →

Train RuView models — camera-free WiFlow pose (10 sensor signals, no labels), camera-supervised pose (MediaPipe + ESP32 CSI → 92.9% PCK@20, ADR-079), RuVector contrastive embeddings (AETHER, ADR-024), domain generalization (MERIDIAN, ADR-027), local SNN environment adaptation, plus GPU training on G

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il y a 5 jDernière mise à jour
Skill
Auteurruvnet
Version0.0.0
LicenceMIT
CatégorieWorkflow
Formatsskill.md
PromptOuvrir (voir l’onglet Prompt)
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Claude✓ Pris en charge
Cursor
Copilot
ChatGPT
Gemini
À propos

Train RuView models — camera-free WiFlow pose (10 sensor signals, no labels), camera-supervised pose (MediaPipe + ESP32 CSI → 92.9% PCK@20, ADR-079), RuVector contrastive embeddings (AETHER, ADR-024), domain generalization (MERIDIAN, ADR-027), local SNN environment adaptation, plus GPU training on GCloud and Hugging Face publishing. Use when building, fine-tuning, evaluating, or shipping a model.

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