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Guides the use of RWKV, a language model architecture that carries information forward in a compact state. Covers streaming text generation, long document processing, fine-tuning, and memory comparisons with Transformers.
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Guides you through setting up RWKV, generating text, processing long documents in chunks, and fine-tuning models. Explains how to carry context between steps and compare memory use with Transformer models.
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Explore how coordinating agents can pass relevant working state to workers through KV cache, a model's internal attention memory. Covers task-specific selection, runtime requirements, and comparisons of accuracy, token use, and processing overhead.
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Configure how Dynamo routes requests to workers, then check model discovery and a chat response. Supports local and Kubernetes setups, including routing based on cached model data, with clear commands, results, and limitations.
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Estimate inference memory for models on Hugging Face Hub without downloading their weights. Check GPU capacity for Safetensors or GGUF files, with optional estimates for the KV cache, memory used to retain attention data during generation.
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Develop and deploy Cloudflare Workers, manage related storage and services, and troubleshoot configuration with Wrangler. The skill checks official documentation and configuration definitions before preparing commands, with guidance for local development, environments, secrets, and logs.
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Investigate slow response starts and low cache reuse in agent applications. The skill explains how to keep instructions and tool definitions stable, append changing information, and preserve message formats so earlier processing can be reused across requests.
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Calculate how to divide serving memory between recurrent state and KV cache, two memory pools used by hybrid models. Use startup logs and workload settings to recommend a ratio, estimate concurrency, and identify the limiting pool.
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Build Splunk pipelines that import threat intelligence and match security events against indicators such as malicious IP addresses, domains, and file hashes. Add source, confidence, and severity details so analysts have context when investigating matches.
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Use when working with Consul Kv — consul KV store management, key namespace analysis, session/lock inspection, and watch configuration. Covers KV tree structure, key count by prefix, session health, prepared queries, and transaction support diagnostics. Read this skill before any Consul KV operations.
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Agent fallback for CCSPlayer_MovementServices_CheckVelocity (auto-generated, category: func). Locate CCSPlayer_MovementServices::CheckVelocity in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CCSPlayer_MovementServices_CheckVelocity, CCSPlayer_MovementServices::CheckVelocity
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OneClickVirt operations skill for managing containers, virtual machines, provider nodes, health checks, and metrics through MCP.
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Implements compliance with Turkey's Personal Data Protection Law (Kisisel Verilerin Korunmasi Kanunu, KVKK, Law No. 6698). Covers data controller obligations, data subject rights, VERBIS registration, cross-border transfer restrictions, Board decisions, and administrative fines. Keywords: KVKK, Turkey, VERBIS, data controller registry, Board decision, cross-border.
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Fix intermittent 500 errors with "Failed to store" in Fastly KV Store during concurrent writes. Use when: (1) Batch operations fail with ~10-20% error rate, (2) Error contains "Failed to store list" or similar KV write failures, (3) Multiple requests updating the same KV key simultaneously, (4) Read-modify-write pattern without locking. The fix is adding a retry loop that re-reads before each write attempt.
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Híbrido RNN+Transformer com inferência O(n). Tempo linear, contexto infinito, sem cache KV. Treina como GPT (paralelo), infere como RNN (sequencial). Projeto Linux Foundation AI. Produção em Windows, Office, NeMo. RWKV-7 (março de 2025). Modelos até 14B parâmetros.
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RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
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Download individual YouTube videos with a chosen quality, file format, and destination folder. Save video as MP4, WebM, or MKV, or download only the audio as MP3 using the included Python script.
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Download individual YouTube videos with a chosen quality, file format, and destination folder. Save video as MP4, WebM, or MKV, or download only the audio as MP3 using the included Python script.
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Build, test, and format CubeSandbox components using make targets and a Docker builder. Also covers the web dashboard’s development workflow, API type synchronization, and troubleshooting for missing services, outdated build tools, and environment requirements.
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Estimate how model architecture, precision, and context length affect weight storage, generation state, computation, and memory traffic. Compare models and attention designs with separate resource estimates for input processing and token generation.
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Compare batching, request scheduling, and memory management for a single model serving instance. Assess concurrent request capacity, response times, generation speed, and GPU time per result that meets the required quality and deadline.
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Für AGB im Bankvertrag Sparkassen und Banken: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: bankvertrag-sparkassen-bauvertrag-vob.
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Für AGB im Bankvertrag Sparkassen und Banken: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: agb-im-bankvertrag-sparkassen-und-banken.
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Migrate Terraform provider resources and data sources from Plugin SDKv2 to the Plugin Framework: muxing both plugins in one provider (terraform-plugin-mux, tf5to6server), per-resource migration workflow, SDKv2-to-Framework schema mapping (ForceNew, ValidateFunc, DiffSuppressFunc, Default, Timeouts, blocks), null-vs-zero-value behavioral traps, and state-compatibility verification. Use when converting or translating SDKv2 resources to the Framework, setting up a muxed provider server, deciding whether a resource should be migrated at all, or debugging plan diffs and state errors that appeared after a migration.
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