'local models' 검색 결과

Answer a hard question by fanning it out to a PANEL of models running in parallel — each answering independently with web search and bash, none seeing the others' work — then having Opus 4.8 judge every response into a structured analysis (consensus, contradictions, partial coverage, unique insights, blind spots) and write a final answer grounded in it. The panel is two independent Opus 4.8 runs (slug opus4.8-4.8), Opus 4.8 + GPT-5.5 via codex (opus4.8-gpt5.5), Opus 4.8 + Gemini 3.1 Pro via agy (opus4.8-gemini3.1pro), or all three (opus4.8-gpt5.5-gemini3.1pro). Opus always judges and writes the final answer — the pipeline can't be reversed. Runs on local CLI subscriptions (no metered API), and saves a timestamped provenance .md per run. Use this whenever the user asks to "run it through Fusion", says /fusion, wants a multi-model / panel / ensemble answer, wants a question cross-checked across models, or wants a higher-confidence answer with consensus and blind spots surfaced — even if they don't say "fusion". General-purpose: any topic (research, law, strategy, technical, personal). Best for high-stakes research, design calls, and debugging where being confidently wrong is expensive.

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Select appropriate Ollama models for processing sensitive but legal content. Use when: (1) llama3.2 or deepseek-r1 refuses to process content with "I cannot assist" responses, (2) Local LLM returns generic safety disclaimers instead of following instructions, (3) Need to process adult content, sex work data, or other legal-but-sensitive material through a local LLM. Also covers using /api/chat vs /api/generate for system prompt support, and structuring prompts for consistent format compliance.

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Generate 3D assets with Tencent's Hunyuan3D family — open-weight self-hosted models (Hunyuan3D-2.0/2.1 and HunyuanWorld / HY-World for scenes) and the hosted, closed API tiers (2.5, PolyGen, 3.0/3.1 via Tencent Cloud and third-party hosts). Use when a task involves image-to-3D or text-to-3D mesh generation, the shape-then-texture (DiT + Paint / PBR) workflow, choosing between self-hosting and a hosted API, checking the Community License's Territory (EU/UK/South Korea) and 1M-MAU commercial gate, sizing GPU/VRAM for local inference, ComfyUI integration, or reviewing and post-processing (retopology, UVs, decimation) the meshes these models produce. Not for image, video, or general LLM tasks.

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健身私教 — 为客户设计、指导和推进个性化训练方案的专业工艺, 有别于团课教练、物理治疗师或运动队教练: (a) 训练方案设计与周期化 (线性 / 波动 / 板块周期化 Bompa & Haff; NSCA《力量训练与体能训练精要》行业圣经; Schoenfeld 肌肥大机制; Helms/Valdez/Morgan 肌肉与力量金字塔; 共轭训练法 Simmons/Westside; Starting Strength 线性渐进 Rippetoe; Renaissance Periodization 训练量地标 Israetel); (b) 动作评估与筛查 (FMS 功能性动作筛查 Gray Cook; NASM CEx 纠正性训练连续体 抑制-拉伸-激活-整合; 关节逐级方法 Cook/Boyle; 姿势与代偿模式识别; PAR-Q+ 与 ACSM 运动前筛查指南); (c) 教学与指令 (外部 vs 内部注意焦点 Wulf; 差异化学习 Schöllhorn; 约束导向方法 Davids/Renshaw; RIR/RPE 自动调节 Zourdos/Helms; 动机访谈在健身中的应用 Rollnick/Miller); (d) 营养指导的执业边界 (宏量营养素周期化; Precision Nutrition / ISSN 立场声明的循证建议; 边界: 私教提供一般性指导, 医学营养治疗需 RD/RDN 资质; 能量可用性与 RED-S Mountjoy IOC 共识); (e) 商业与客户管理 (客户留存与方案依从; 咨询与销售伦理; 线上教练平台与规模化 Goodman PTDC; 方案交付工具 TrueCoach/Trainerize/TrainHeroic; 课时定价模型; 独立教练 vs 健身房雇员); (f) 专项方向 (运动表现 CSCS; 纠正性训练 CES; 老年健身 SFN; 产前产后; 青少年 YSCA; 适应性 / 无障碍健身; 健美 / 形体; 力量举; 耐力运动 S&C)。诚实处理: 兄弟科学 vs 循证之争, 补剂行业利益冲突, 合成代谢激素使用现状 (诚实但不推广: 匿名调查约 30% 有经验男性健身者使用过 — 业内估, Kanayama/Pope/Hudson 记录健康风险, WADA 禁用清单用于竞技语境), 体型焦虑与进食障碍风险 (男性私教肌肉变形症, 正食症倾向, NEDA 负责任语言指南), 健身房掠夺性销售 (高压推销、误导性对比照、长约锁定), 执业边界违规 (私教诊断伤病或超范围开饮食处方), 线上教练认证造假 (周末速成、未经认可的认证)。不含: 物理治疗 / 康复治疗 (持照医疗职业), 不含: 团课教练 (Les Mills/Zumba/CrossFit 分馆教练 — 相邻但不同), 不含: 精英竞技运动教练 (团队项目周期化, 不同职业路径), 不含: 营养作为主业 (临床营养学需单独资质)。 (Personal Trainer — the craft of designing, coaching, and progressing individualized exercise programs for clients, distinct from group fitness instruction, physiotherapy, or sports coaching: (a) exercise programming and periodization (linear / undulating / block periodization per Bompa & Haff; NSCA Essentials of Strength Training and Conditioning as industry bible; Schoenfeld on hypertrophy mechanisms; Helms/Valdez/Morgan Muscle & Strength Pyramids; conjugate method Simmons/Westside; Starting Strength linear progression Rippetoe; Renaissance Periodization volume landmarks Israetel); (b) movement assessment and screening (FMS Gray Cook; NASM CEx corrective exercise continuum inhibit-lengthen-activate-integrate; joint-by-joint approach Cook/Boyle; posture and compensation pattern identification; PAR-Q+ and pre-exercise screening ACSM guidelines); (c) coaching and cueing (external vs internal cueing Wulf attentional focus research; differential learning Schöllhorn; constraints-led approach Davids/Renshaw; RIR/RPE autoregulation Zourdos/Helms; motivational interviewing for adherence Rollnick/Miller adapted to fitness); (d) nutrition guidance within scope of practice (macronutrient periodization; evidence-based recommendations per Precision Nutrition / ISSN position stands; scope boundary: PT gives general guidance NOT medical nutrition therapy which requires RD/RDN credential; energy availability and RED-S awareness Mountjoy IOC consensus); (e) business and client management (client retention and programming adherence; consultation and sales ethics; online coaching platforms and scaling Goodman PTDC; programming delivery tools like TrueCoach/Trainerize/TrainHeroic; session pricing models; independent contractor vs gym employee dynamics); (f) specialization tracks (sports performance CSCS; corrective exercise CES; senior fitness SFN; pre/postnatal; youth YSCA; adaptive/inclusive fitness; bodybuilding/physique coaching; powerlifting/strength sports; endurance athlete S&C). Evidence-based practice as the core ethos: Schoenfeld/Krieger meta-analyses on volume-response, Helms systematic reviews on protein/resistance training, Brad Schoenfeld's MASS journal bridging research to practice, Menno Henselmans and Eric Helms as practitioner-researchers, Greg Nuckols Stronger By Science as translation layer. Chinese fitness industry context: rapid growth of personal training in commercial gyms (Keep/Lefit/Megafit chains), NSCA-CPT and ACE-CPT as dominant certifications alongside local CSFA (China Sport and Fitness Association) credential, '体适能' (physical fitness) as formal term, online coaching boom post-COVID, PT business models in tier 1-3 cities diverge sharply. Honest treatment of: bro science vs evidence-based d

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Run coding tasks via opencode using free cloud models. Use when asked to offload work to opencode.ai or run a free model. Don't use for local models (Ollama, LM Studio), Claude/OpenAI calls, or when Claude should do the work itself.

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Design local AI engines for iOS. Use when wiring Apple Foundation Models, local classifiers, extraction, summarization, grounded answers, and cloud fallbacks.

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Runs local and self-hosted LLMs with Ollama, LM Studio, MLX, llama.cpp, and Open WebUI. Use when choosing GGUF quants, sizing VRAM, or running models privately.

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Get external agent review and feedback. Routes Anthropic models through Claude Agent SDK (uses local subscription) and other models through OpenRouter API. Use for code review, architecture feedback, or any external consultation.

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List configured models, guide provider setup, verify local Kimi companion readiness, and manage the PreToolUse hook plus optional review gate. Use when asked about available models, subscription/API-key setup, default selection, or explicitly requested to install, check, enable, disable, or uninstall the integration. Codex and Claude Code share one ~/.kimi-code/config.toml but each own a host-scoped block, so $kimi-setup here does not disturb Claude Code's /kimi:setup (and vice-versa).

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Scientific model and eval tuning loop for prompt/skill/system-prompt changes, model configuration, runtime options, and local/Ollama model sizing or environment variables. Use when tuning eval performance, comparing local or remote models, improving tool-use behavior, reducing timeouts/loops, or deciding whether an eval optimization is worth keeping.

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Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

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Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.

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Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.

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Hermes Agent (Nous Research の AI CLI エージェント)。インストール、 CLI コマンド (chat, model, gateway, config, cron, webhook, mcp, skills, profile, hermes pm)、 Configuration (Terminal Backends, Memory, TTS / STT, Auxiliary Models, Compression, Display, Local Models llama.cpp, Egress / Secrets)、 Features (Tools, Skills, Hooks, Delegation, Kanban, Cron, Voice Mode, Personality, Context Files)、 Messaging Gateway (Platform Support, Bot Mode, Connectors)、Security、Architecture、 Hermes Desktop、Plugin Catalog、Profiles、Developer Guide、Nous Portal (Tool Gateway)。

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Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.

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Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

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Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.

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Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.

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Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.

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로그와 재현 작업으로 OpenClaw의 모델 통신과 도구 실행 문제를 조사합니다. 저장된 대화와 첨부 자료도 확인하여 원인 수정과 재검증에 필요한 근거를 모읍니다.

• 로컬 테스트와 실제 서비스의 동작 차이 조사
• 모델이 실제로 볼 수 있는 도구 확인
• 응답 스트리밍 지연과 중단 조사

VoiceStudio를 에이전트와 자동화에 연결해 저장된 목소리로 음성을 생성하고 녹음을 텍스트로 옮깁니다. 자막, 더빙, 내레이션을 제작하고 결과 파일을 확인합니다.

• 저장된 목소리로 내레이션 생성
• 녹음의 텍스트 변환과 자막 제작
• 발화 시점과 배경음을 보존하는 더빙

Develop machine learning models from local data, covering data preparation, model selection, training, evaluation, and deployment preparation. Use it to build workflows for tasks such as predicting customer churn or classifying images.

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• Building a model to predict customer churn
• Training a neural network for image classification
• Preparing missing values and categorical data for training

거래 전략의 장기 검증, 여러 조건 비교와 모델 학습을 클라우드에서 수행합니다. 비용 추정부터 성과 지표와 CSV 수집, 결과 서명 검증과 저장까지 지원합니다.

• 거래 전략의 여러 해 성과 검증
• 다양한 매개변수 조합 비교
• 클라우드에서 LSTM 등 모델 학습

준비된 테스트 사례로 agent-booster의 성공률과 작업 분배를 검증합니다. 선택적으로 외부 모델과 비교하고 실측 결과와 집계를 JSON으로 저장합니다.

• 출시 전 성공률 확인
• 테스트 사례 추가 후 작업 분배 검증
• 실측 결과로 성능 설명 확인