Clean training loops with built-in distributed support.
Distributed training orchestration across clusters.
Debug and optimize AI agents by analyzing reasoning traces, context degradation, tool confusion, instruction drift, repeated task…
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure.
SAM: zero-shot image segmentation via points, boxes, masks.
Semantica full-stack knowledge graph skill for context graphs, decision intelligence, explainability, extraction, reasoning…
Analyze cause-and-effect relationships in the Semantica knowledge graph — causal chains, interventions, counterfactuals, and causal…
Generate, inspect, and use node/text embeddings in Semantica — compute Node2Vec embeddings, find similar nodes, score link predictions…
Explain Semantica reasoning, decision logic, and graph results with traceability, causal context, and human-readable rationale.
Export Semantica graphs, results, and provenance to JSON, RDF, Parquet, CSV, GraphML, and other formats.
Run the full Semantica semantic extraction pipeline on a file or selected text — NER, relations, events, coreference resolution, triplets…
Trace data lineage, source attribution, audit trails, and provenance assertions in Semantica graphs.
Run reasoning over the Semantica knowledge graph — deductive logic, abductive hypothesis generation, Datalog programs, SPARQL queries…
Validate Semantica pipelines, extraction quality, graph schemas, and ontology consistency.
Visualize the Semantica knowledge graph — topology, centrality, communities, paths, embeddings, decision insights, and temporal evolution.
Reference-free preference alignment, simpler than DPO.
RL post-training for LLMs with Megatron and SGLang.
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
Text-to-image generation, inpainting, and img2img.
Audit PostHog survey SDK features and version requirements