Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
中文简介正在准备中。当前显示原文说明。
Route AlphaGPT data ingestion, factor mining, live strategy, and dashboard workflows.
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
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.还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
中文简介正在准备中。当前显示原文说明。
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
中文简介正在准备中。当前显示原文说明。
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
中文简介正在准备中。当前显示原文说明。
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
中文简介正在准备中。当前显示原文说明。