Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Router for Alpamayo R1 multimodal driving inference and trajectory sampling.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Use this skill for Alpamayo R1 inference on PhysicalAI-AV clips: load one clip, build the multimodal prompt, run the model on CUDA, inspect reasoning traces, and compare predicted trajectories to ground truth.
Use a Python 3.12 CUDA environment with the package dependencies installed, then perform a minimal import check from outside the checkout:
python -m pip install -e <repo-checkout>
python -I -c "import alpamayo_r1, torch; print(alpamayo_r1.__name__); print(torch.cuda.is_available())"
If the editable install or import fails, open references/troubleshooting.md before changing the workflow.
sub-skills/inference/SKILL.md — the end-to-end driving inference workflow, including dataset loading, prompt creation, model sampling, output interpretation, and the bundled smoke script.references/repo-provenance.md — source commit, version, and evidence paths used to build this skill.references/repo-routing-metadata.json — structured router metadata consumed during repo-skill import.references/troubleshooting.md — cross-cutting install/import/backend guidance.sub-skills/inference/SKILL.md.sub-skills/inference/scripts/run_inference_smoke.py for a runnable sample.references/troubleshooting.md.还没有评价。欢迎分享你的使用感受。
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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.
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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.
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.
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