modal-serverless-gpu

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Tool: SKILL.md Description: --- name: modal-serverless-gpu description: Serverless GPU cloud platform for running ML workloads.

Malicious tool definition detected

Tool: references/advanced-usage.md [1/2] Description: # Modal Advanced Usage Guide ## Multi-GPU Training ### Single-node multi-GPU ```python import modal app = modal.App("multi-gpu-training") image = modal.Image.debian_slim().pip_install("torch", "transformers", "accelerate") @app.function(gpu="H100:4", image=image, timeout=7200) def train_multi_gpu(): from accelerate import Accelerator accelerator = Accelerator() model, optimizer, dataloader = accelerator.prepare(model, optimizer, dataloader) f

Tool: references/advanced-usage.md [2/2]

Malicious tool definition detected

Tool: references/troubleshooting.md [1/2] Description: # Modal Troubleshooting Guide ## Installation Issues ### Authentication fails **Error**: `modal setup` doesn't complete or token is invalid **Solutions**: ```bash # Re-authenticate modal token new # Check current token modal config show # Set token via environment export MODAL_TOKEN_ID=ak-...

Tool: references/troubleshooting.md [2/2] Description: ```python @app.function(gpu="T4") def debug_environment(): import subprocess import sys # System info print(f"Python: {sys.version}") print(subprocess.run(["nvidia-smi"], capture_output=True, text=True).stdout) print(subprocess.run(["pip", "list"], capture_output=True, text=True).stdout) # CUDA info import torch print(f"CUDA available: {torch.cuda.is_available()}") print(f"CUDA version: {torch.version.cuda}") print(f"GPU: {torch.cuda.get_dev