'language' 검색 결과

Guides image classification and search with OpenAI's CLIP by comparing images with text descriptions, without additional training. Includes batch processing, image-text matching, and category-based checks for potentially inappropriate images.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Classify images using text labels without additional training
• Search an image collection with natural-language descriptions
• Compare how closely images match text descriptions

Build text tokenizers, which split text into units for AI models, directly from raw multilingual text. Learn custom vocabularies with BPE or Unigram, convert text to pieces or numeric IDs, and decode the results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing text for multilingual AI models
• Training a vocabulary from Japanese text
• Reusing a tokenizer for reproducible text splitting

Create a translated copy of a Canva design by replacing text across all pages in the requested language. Keep the original intact, preserve formatting cues, and review a preview before approving the translated design for saving.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a French version of a sale poster
• Translating text across a multipage Canva design
• Making another language version while keeping the original

Collect Trustpilot reviews for a company domain, with filters for ratings, language, dates, and reply status. Get structured review text, reviewer details, and company responses across pages to support reputation research and customer service analysis.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Collect low-rated reviews to study customer complaints
• Gather reviews for competitor reputation comparisons
• Collect company replies and their publication dates

Find language-specific guidance files for a code-testing pipeline. This reference catalog points agents to build and test commands, mocking patterns, common errors, and selected workflow examples across languages including .NET, Python, TypeScript, Go, and Java.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding test guidance for a project's programming language
• Locating build commands and test framework guidance
• Finding mocking patterns and common error references

Run small C# apps without creating a project, using the .NET CLI, its command-line tool. Use it to test language features, explore APIs, or prototype utilities with helper files and NuGet packages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Trying C# language features or APIs
• Prototyping logic before project integration
• Building a small utility with helper files

Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners. Use when adapting tasks, planning support, or assessing linguistic accessibility.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate tiered sentence frames for academic tasks that scaffold language production across proficiency levels. Use when EAL students need structured language support for classroom discourse.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert knowledge for Azure AI Language development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using CLU, custom/health NER, CQA, sentiment/PII APIs, or Language/TA/health containers, and other Azure AI Language related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure AI Document Intelligence (use azure-document-intelligence), Azure Speech in Foundry Tools (use azure-speech), Azure Translator (use azure-translator).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Creates language variants of existing Semgrep rules. Use when porting a Semgrep rule to specified target languages. Takes an existing rule and target languages as input, produces independent rule+test directories for each language.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Write modern, version-aware C# for .NET repositories while staying compatible with the repo's target framework and language-version policy. USE FOR: modern idiomatic C# code; language-version compatibility decisions; upgrading or reviewing C# feature usage across versions. DO NOT USE FOR: non-C# .NET languages such as F# or VB; analyzer-only or formatter-only setup with no language feature choice. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Write content in any language indistinguishable from a skilled human writer. Avoids AI-sounding phrases, varies sentence structure, creates natural prose. Detects target language and loads language-specific AI-tells, register, and orthography from `languages/`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract programming-language-agnostic pseudocode from source code in any language, preserving control flow and logical structure while filtering out implementation details. Use when the user asks to convert code to pseudocode, abstract code logic, understand code structure without syntax, create language-independent documentation, or analyze algorithmic flow without language-specific details.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Audit any Lattice SKILL.md for language compliance — removes rationale prose, converts soft language to imperatives, adds STOP: gates on hard rules, and cuts redundant repetition. Complements skill-review (which finds behavioral gaps) by fixing phrasing that causes agents to skip or underweight instructions at runtime. Use after writing or significantly changing any skill, or when the user says 'tighten this skill', 'clean up the language', 'make this more effective', 'reduce the bloat', 'tighten the language', or 'skill tighten'. Standalone — does not call other skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners. Use when adapting tasks, planning support, or assessing linguistic accessibility.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate tiered sentence frames for academic tasks that scaffold language production across proficiency levels. Use when EAL students need structured language support for classroom discourse.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before building or running the workflow; or build custom language/messaging from buyer, competitor, community, and CRM evidence. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Research the etymology of a word by tracing proto-language roots, identifying cognates across language families, documenting semantic drift with dated attestations, and flagging folk etymologies. Use when investigating word origins, comparing cognate sets across related languages, charting historical meaning changes, or debunking popular but unsupported origin stories.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Systematic methodology for achieving 100% backward dataflow reachability in a new language. Create gauntlet fixture, write trace, diagnose gaps, fix analyzer/algorithm, iterate to 100%. Language-agnostic process. Use when: (1) adding a new language to Grafema, (2) auditing dataflow coverage for existing language, (3) user says "/dataflow-gauntlet".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hreflang and international SEO audit, validation, and generation. Detects common mistakes, validates language/region codes, and generates correct hreflang implementations. Use when user says "hreflang", "i18n SEO", "international SEO", "multi-language", "multi-region", "language tags", "language targeting", "country targeting", "x-default", "locale", or "multilingual SEO".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.