オープンウェイトモデルのトレーニングと推論のためのエンドツーエンドインフラストラクチャ
End-to-end infrastructure for training and inferencing open weight models (docs.appliedcompute.com)
要約
Applied Compute Agent Cloud (AC2) は、モデル開発、推論、継続学習をエンドツーエンドで行うための研究者向けコックピットです。コーディングエージェントを利用したセットアップや、SDK、ランタイム、トレーシングといったパッケージ、評価、トレーニング、推論ルーティングなどのワークフローを提供します。これにより、研究者は効率的にAIモデルの開発と運用を行うことができます。
全文翻訳
End-to-end infrastructure for training and inferencing open weight models
Applied Compute Agent Cloud (AC2) is a researcher cockpit for end-to-end model development, inference and continual learning.
Onboard with your coding agent
Paste this prompt into Claude Code, Cursor, Codex, or any coding agent:
Fetch https://platform.appliedcompute.com/agents.md (e.g. curl -fsSL https://platform.appliedcompute.com/agents.md) and follow its instructions to set up AC2 for me.
The agent installs the CLI, logs you in, wires up the AC2 MCP server, and walks you through your first project. Prefer to run the steps yourself? Follow the Quickstart.
Packages
ac2.sdk— platform client for datasets, workloads, sessions, traces, and secrets.ac2.runtime— agent framework for agents, environments, orchestrators, tasks, graders, and episodes.ac2.tracing— OpenTelemetry-based observability SDK. Add@tracedto any function to capture timing, inputs, outputs, and nested spans. Exports to ClickHouse and Langfuse.
Quickstart
Install the SDK and train a model.
Runtime
Define agents, environments, orchestrators, and eval tasks.
SDK
Manage datasets, deployments, runs, traces, and secrets from Python.
MCP server
Analyze eval and train traces from your editor.
Choose a workflow
Evaluate an agent
Run evals, grade traces, and compare behavior.
Train a model
Choose GRPO, supervised fine-tuning, or on-policy self-distillation.
Route inference
Deploy a model and route traffic through Policies and Endpoints.
FAQ
Find answers for failed runs, datasets, package installation, and cleanup.