Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Use Docling to convert, parse, configure, extract, chunk, serve, and maintain document-processing workflows across Python APIs, CLI commands, optional pipelines, and repository edits.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Use this skill when a task involves Docling, the Python SDK and CLI for converting PDFs, Office documents, HTML, Markdown, images, audio/video, XML, CSV, and other sources into DoclingDocument for downstream AI workflows.
references/install-and-environment.md when choosing docling vs docling-slim, optional extras, Python versions, model artifacts, or safe environment checks.references/repo-provenance.md before deciding whether this skill matches a current checkout or should be refreshed.references/troubleshooting.md for cross-cutting install/import, optional dependency, model download, CLI/API, remote-service, and repository-edit failures.| User task | Use sub-skill | Why |
|---|---|---|
| Convert a local file, URL, binary stream, or in-memory Markdown/HTML/DocLang string with Python | sub-skills/conversion/SKILL.md | Owns DocumentConverter, convert, convert_all, convert_string, DocumentStream, limits, headers, and conversion failures. |
Build or explain docling local CLI commands and supported formats | sub-skills/cli-and-formats/SKILL.md | Owns docling convert, --from, --to, output directories, image export/fetch modes, and command construction. |
| Tune the standard PDF pipeline, OCR, table structure, accelerators, artifacts, and option models | sub-skills/pipeline-configuration/SKILL.md | Owns PdfPipelineOptions, OCR/table options, artifacts_path, AcceleratorOptions, and option validation. |
Export, serialize, chunk, or post-process an existing DoclingDocument | sub-skills/document-outputs/SKILL.md | Owns Markdown/JSON/YAML/HTML/Text/DocTags/WebVTT exports, image modes, table extraction, and RAG chunking. |
| Use VLM, ASR/audio-video, enrichments, advanced model backends, GPU/MLX, or offline model prefetch | sub-skills/advanced-pipelines/SKILL.md | Owns VlmPipeline, AsrPipeline, enrichment flags, model catalog decisions, optional extras, and no-download preflights. |
Call a running docling-serve endpoint or use docling convert-remote/service client SDK | sub-skills/remote-service-client/SKILL.md | Owns service URL/API key handling, remote CLI, sync/async client, batches, jobs, chunk endpoints, and network-safe checks. |
| Extract structured fields from documents | sub-skills/extraction/SKILL.md | Owns DocumentExtractor, extraction templates/options/results, and VLM extraction caveats. |
| Modify the Docling repository itself | sub-skills/repo-maintenance/SKILL.md | Owns package layout, extras, CLI/docs generation, tests, validation, and repository-specific agent rules. |
pip install docling for typical users; install docling-slim with extras only when intentionally composing a smaller environment.>=3.10,<4.0.docling CLI exposes local convert behavior and remote convert-remote behavior; bare docling SOURCE routes to local conversion.docling-tools models download prefetches model artifacts for offline/local use, but it can download large files; do not run it unless the user wants model downloads.DocumentConverter, DocumentExtractor, InputFormat, OutputFormat, pipeline option classes, HybridChunker, and DoclingServiceClient.--help, and tiny local fixtures.enable_remote_services=True; for docling-serve conversion, route to remote-service-client.AGENTS.md, run focused tests for touched behavior, and run make validate before considering the change complete when feasible.scripts/check_docling_environment.py checks package importability, CLI availability, optional modules, and common external binaries without converting documents or downloading models.conversion, then use document-outputs if the user needs Markdown/JSON/HTML/chunking/table files.cli-and-formats, then use pipeline-configuration for OCR/table/model flags or advanced-pipelines for VLM/ASR/enrichment choices.remote-service-client; do not upload documents during preflight unless the user authorizes a live service call.repo-maintenance; do not use public runtime examples as a substitute for repository tests.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
日本語の概要は準備中です。原文の説明を表示しています。
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
日本語の概要は準備中です。原文の説明を表示しています。
Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
日本語の概要は準備中です。原文の説明を表示しています。
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
日本語の概要は準備中です。原文の説明を表示しています。