Results for “trello”

Manage Trello boards, lists, and cards via the Trello REST API.

Manage Trello boards, lists, and cards via the Trello REST API.

Manage Trello boards, lists, and cards directly from the command line using curl and the Trello REST API.

Manage Trello boards, lists, and cards via the Trello REST API.

Trello REST API skill. Use when working with Trello REST for actions, applications, batch. Covers 256 endpoints.

Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning) with support for SFT, DPO, GRPO, KTO, RLOO, and reward model training via CLI commands.

Load 3D models, textures, and HDR environments in Three.js with GLTF, OBJ, FBX, STL, PLY, and Draco/KTX2 compression support.

Fine-tune and align language models using reinforcement learning with TRL, including SFT, DPO, PPO, GRPO, and reward model training.

Use when building or debugging interactive 3D scenes on the web with Three.js (scene/camera/renderer, lights/materials, GLTF loading, controls, performance). Helpful for designers shipping 3D UI moments.

Manages software projects end-to-end — decomposing work into tasks, tracking progress across sprints, generating status reports, and integrating with tools like Jira, Linear, GitHub Issues, and Trello. Use when the user requests project management or provides relevant inputs for this workflow.

Reduce per-token latency on Jetson vLLM servers by appending speculative decoding configuration, with guidance on when to enable and how to benchmark the improvement.

Configure fault tolerance, straggler detection, preemption, in-process restart, and re-run state machine for Megatron Bridge training jobs.

Train or fine-tune language and vision models using TRL or Unsloth on Hugging Face Jobs cloud infrastructure, with support for SFT, DPO, GRPO, and reward modeling, plus GGUF conversion for local deployment.

Train, evaluate, distill, quantize, export, and run inference for RT-DETR object detection models using NVIDIA TAO.

Train, evaluate, export, quantize, and run inference for a Deformable DETR 2D object detection model using TAO, with deformable attention for efficient multi-scale feature processing.

Write and run Perl tests using Test2::V0, Test::More, prove, mocking, and Devel::Cover with a TDD workflow.

Write and run Perl tests using Test2::V0, Test::More, prove, mocking, and coverage analysis with Devel::Cover, following a TDD workflow.

Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.

Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology.

Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.

Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

Train LLMs with reinforcement learning using verl (Volcano Engine RL), supporting RLHF, GRPO, PPO, and other algorithms for scalable post-training with flexible infrastructure backends.

Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology.

Move issues and external pull requests through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.

Fetches real-time London transit data from the TfL API, including Tube and bus arrivals, line status, disruptions, journey planning, and route information.

Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology.

Trigger: tech stack, preferred tools, SvelteKit, Bun, Drizzle, Zero Sync, Better Auth, Vite. Scope: Project tooling preferences, framework selections. Boundary: Excludes application logic or visual styling guidelines.

Audits trending open-source repos for exploitable vulnerabilities using Semgrep, TruffleHog, osv-scanner, and Slither, then routes findings to responsible disclosure channels (PVR for code flaws, public PRs for dependency CVEs).

Three.js asset loading - GLTF, textures, images, models, async patterns. Use when loading 3D models, textures, HDR environments, or managing loading progress.

使用Test2::V0、Test::More、prove runner、模拟、Devel::Cover覆盖率和TDD方法的Perl测试模式。

Threat modeling workflow for software systems: scope, data flow diagrams, STRIDE analysis, risk scoring, and turning mitigations into backlog and tests. Use when designing new features, reviewing architecture changes, handling sensitive data, or hardening auth/payment/multi-tenant flows.