AIエージェント
agent-native
A framework for building agentic apps
★ 7.0k スターUnknown
ガイドを見る →labs-moltは、NVIDIA-NeMoが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: NVIDIA-NeMo/labs-molt）。GitHubスターは1,171、フォークは113で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2026年10月7日です。
A lean, HuggingFace-native RL framework for agentic research.
Choose one real workload to test the project against.
Clone it locally and read through the getting-started guide.
Install the stack it needs and set any environment variables.
Execute the starter example and check results before going further.
Reinforcement learning designed for agent training.
Built on the HF ecosystem.
9k lines — readable and hackable.
FSDP and parallelism support.
From NVIDIA's NeMo team.
Permissive licensing.
Download the source and move into the project folder.
git clone https://github.com/NVIDIA-NeMo/labs-molt.git
cd labs-moltSet up a Python environment with the training dependencies.
pip install -r requirements.txt
# check README for torch/CUDA requirementsRun a training example per the README.
# needs GPU — see README for the example configsIt is maintained by NVIDIA-NeMo at NVIDIA-NeMo/labs-molt, with 113 forks.
Yes. It is released under the Apache-2.0 license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
No — but RL training needs serious GPU compute, and that is the real cost.
Compare on simplicity and HuggingFace integration — its 9k-line scope is the differentiator.
Check the GPU requirements, install dependencies, and follow the training examples.
A framework for building agentic apps
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