Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Route AlphaGPT data ingestion, factor mining, live strategy, and dashboard workflows.
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Review the instructions the agent will receive before you install.
Use this repo skill for the AlphaGPT crypto-quant system. It helps future agents work with the repository's four main workflows without reopening the source tree for basic navigation:
python -m pip install -r requirements.txt.pyproject.toml/setup.py distribution, so use the checkout itself as the import root when validating a local clone.execution.trader fails on the newest Solana wheel because TokenAccountOpts is missing, consult the live-strategy troubleshooting notes for the verified solana==0.36.12 and websockets==15.0.1 compatibility pin.data_pipeline, model_core, execution, strategy_manager, and dashboard.From a checkout that is on PYTHONPATH or otherwise visible to the environment, a safe smoke check is:
python -I -c "import data_pipeline, model_core, execution, strategy_manager, dashboard"
If you need a deeper no-network preflight, use the bundled env checker instead of touching databases, RPC endpoints, or wallets.
requirements-optional.txt unless you explicitly choose the optional research workflows.references/repo-provenance.md and compare the current checkout before deciding whether to refresh this skill.No reviews yet. Tell others what you thought.
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Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
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Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
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Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
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Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
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Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
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