For reinforcement learning training pipelines where AI-generated code is evaluated in sandboxes across potentially untrusted workers, the threat model is both the code and the worker. You need isolation in both directions, which pushes toward microVMs or gVisor with defense-in-depth layering.
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Download a NeMo checkpoint from NVIDIA and convert to safetensors:
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Backpressure is strict by default. When a buffer is full, writes reject rather than silently accumulating. You can configure alternative policies — block until space is available, drop oldest, drop newest — but you have to choose explicitly. No more silent memory growth.