prompt: Explain why persistent volumes are useful for checkpoints in a Modal fine-tune.

text: - Persistent volumes are useful for checkpoints in a Modal fine-tune because they provide a way


prompt: Give a one-sentence explanation of why Modal secrets should hold Hugging Face tokens.

text: - Hugging Face tokens are a set of pre-trained language models that can be used to fine


prompt: List the minimal artifacts you would keep for a short GPU benchmark slice.

text:
Include a brief explanation of why you chose these artifacts.

Include a brief explanation of how you would


prompt: Which GPU is the default choice for a small LoRA run and why?

text: The default choice for a small LoRA run is the NVIDIA Jetson TX2. This GPU


prompt: What should be validated after resuming from a saved checkpoint?

text:
- The user's progress in the game
- The game's difficulty level
- The game'


prompt: Why should a benchmark save hashes and file sizes for artifacts?

text: Because benchmarking is a crucial part of software development, and it helps to identify bottlenecks


prompt: In one sentence, explain the quality-vs-compression tradeoff in KV cache compaction.

text:
- KV cache compaction is a tradeoff between quality and compression.
- Quality refers to the


prompt: Why does a MoE router need a load-balance loss?

text: A MoE router needs a load-balance loss because it is designed to distribute traffic evenly across


prompt: What is the role of EWC when adapting with LoRA?

text: EWC plays a crucial role in adapting with LoRA by providing a reliable and secure communication channel


prompt: What does a JEPA-style objective optimize compared with token reconstruction?

text: A JEPA-style objective optimizes the probability of correctly reconstructing the original image from the reconst


prompt: Which latency signals are mandatory in a short cloud-GPU proof run?

text:
A. Latency of the GPU to the CPU
B. Latency of the CPU to the