8,121 件 ・ 関連度順
Guide DeepMedic 0.8.4 workflows for multi-modal 3D NIFTI medical-image segmentation, including data preparation, model configuration, training, checkpoint continuation, inference, and CPU/CUDA 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。
Use denoising-diffusion-pytorch for PyTorch DDPM/DDIM image diffusion, 1D sequence diffusion, conditioning and guidance, and advanced diffusion variants.
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 Det3D PyTorch 3D object-detection workflows across configuration, KITTI/nuScenes/Lyft data preparation, GPU training and evaluation, custom CUDA operations, 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。
Guides ChatGLM2-6B Transformers inference, local demos, FastAPI/OpenAI-compatible serving, C-Eval evaluation, and P-Tuning v2 fine-tuning.
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。
Guides CLIP-as-service client, server, and CLIP search workflows for text/image embeddings, cross-modal ranking, and retrieval services.
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。
Guides core Autodistill workflows for foundation-model auto-labeling, target-model distillation, CLI/plugin registry use, custom model interfaces, and utilities.
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。
Guides Attention-Gated Networks PyTorch medical imaging workflows for ultrasound classification, attention-gated U-Net segmentation, data layout, CUDA setup, and visualization helpers.
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 Baichuan-7B model loading, architecture inspection, C-Eval/MMLU evaluation preflights, and DeepSpeed pretraining setup from self-contained repo guidance.
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。
CPU-only operating guidance for the BEHAVIOR-1K BDDL 3.7.0 package: symbolic activity definitions, condition parsing/evaluation, object taxonomy, and generated-data-backed knowledge-base inspection.
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。
Guides CUDA-based BigGAN-PyTorch training, checkpoint sampling, dataset preparation, metric preparation, model customization, and optional TensorFlow Hub weight conversion.
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 CUDA-enabled BindCraft protein-binder design from target PDB preparation through AF2/MPNN/PyRosetta execution, filtering, output analysis, and conservative 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 AutoGPT Platform self-hosting, backend, frontend, and legacy Classic agent work to focused operating guidance.
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 substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.
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。
Guide agents through AgiBot X1 humanoid reinforcement-learning training, checkpoint playback, policy export, and MuJoCo sim2sim workflows with verified configuration contracts and explicit Isaac Gym limits.
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 AIMET install, PyTorch/ONNX quantization, GenAILab, model access, cluster/Pod, Qualcomm SDK, optimization, export, and repository tasks to focused operating guidance.
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 AlpaSim repository guidance for autonomous-driving simulation setup, Hydra wizard runs, runtime services, ego drivers and plugins, ASL evaluation, controller/physics/traffic components, gRPC contracts, and operational 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。
Guide alphafold2-pytorch protein sequence, MSA, distogram, angle-logit, coordinate-refinement, recycling, embedding, and structure-utility workflows with version-aware 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。
Guides Any4LeRobot dataset conversions, LeRobot-to-RLDS export, and LeRobot v1.6-v3.0 format migrations with schema validation, version-aware environments, and safe publication boundaries.
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。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
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。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.
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。
Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
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。
Capture a Burp Suite Repeater request/response as a PoC image (targets/<eng>/poc/) by driving the Burp MCP + the Kali GUI. Replays a request in a Repeater tab, sends it, and grabs the request+response panes - a Burp-native PoC (client report / CTF writeup). Use when you want the evidence to come from Burp rather than a curl/terminal card, or whenever you drive a target through Burp and need the images. Pairs with hunt-burp.
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。
Build or revise Godot UI from an approved design, separated art, or a visual reference when scene structure, gameplay binding, and runtime visual verification all matter. Use for complete Godot UI integration; use ordinary Godot UI guidance for isolated node or layout questions that do not require an end-to-end visual workflow.
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。