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cccskills

Results for “monarch”

6 skills · sorted by relevance

Set up model training with torchforge for reinforcement learning, where rewards guide improvement. Covers training configurations, custom reward and loss functions, and distributed execution with Monarch and TorchTitan, keeping algorithm experiments separate from infrastructure concerns.

  • Train mathematical reasoning models with GRPO
  • Experiment with custom reward and loss functions
  • Scale training across multiple GPUs or nodes
davila7/claude-code-templates32.8KUpdated Oct 20, 2026

Guides reinforcement learning, where models learn from rewards, using torchforge and PyTorch. Covers reward design, custom loss functions, and distributed training so researchers can experiment with algorithms while keeping infrastructure concerns separate.

  • Train mathematical reasoning models with GRPO
  • Experiment with custom loss functions
  • Scale training across multiple GPUs or nodes
Orchestra-Research/AI-Research-SKILLs13.7KUpdated Oct 11, 2026

Query Monarch Initiative for disease-gene-phenotype associations

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paperclipai/companies928Updated Mar 24, 2026

Monarch Initiative knowledge graph REST API for disease-gene-phenotype associations and cross-species orthology. MONDO disease-to-gene/phenotype, HP phenotype profiles, cross-species comparisons. Use for rare disease gene prioritization and phenotype-based candidate ranking. For GWAS use gwas-database; for clinical pathogenicity use clinvar-database.

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jaechang-hits/SciAgent-Skills381Updated Oct 16, 2026

Fornece orientação para treinamento RL agentico nativo do PyTorch usando torchforge, biblioteca da Meta que separa infraestrutura de algoritmos. Use quando você quer abstrações limpas de RL, fácil experimentação de algoritmos, ou treinamento escalável com Monarch e TorchTitan.

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artubss/SKILLS-CLAUDE-CODE11Updated May 17, 2026

Retrieve mouse phenotype data from the Jackson Laboratory Mouse Phenome Database (MPD) via its REST API. Browse 520+ projects, look up per-project measure metadata, pull strain-level means (raw or LS-mean adjusted) and per-animal values, find measures by MP/VT ontology terms, and resolve strain nomenclature or gene coordinates. Use for QTL support, cross-strain comparison, mouse model selection, and ontology-driven phenotype discovery. Use monarch-database for disease-gene-phenotype knowledge graphs; ensembl-database for mouse genome annotations.

The English summary is being prepared. Showing the original description.

jaechang-hits/SciAgent-Skills381Updated Oct 16, 2026