ACT

ACT(Action Chunking with Transformers)是面向机器人学习场景的高性能端到端动作控制模型。相比传统模块化机器人控制模型,ACT采用轻量化Transformer架构作为核心骨干进行动作表征学习,结合多模态感知融合模块和时序动作优化网络,在控制精度和实时响应速度上均有显著提升。

Mirror Metadata

  • Hugging Face repo: shadow-cann/hispark-modelzoo-act
  • Portal model id: ivcifqkd0400
  • Created at: 2026-03-03 10:30:33
  • Updated at: 2026-03-04 16:06:22
  • Category: 多模态

Framework

  • PyTorch

Supported OS

  • OpenEuler

Computing Power

  • Hi3403V100 SVP_NNN

Tags

  • 具身智能

Detail Parameters

  • 输入: 1 x 6;1 x 3 x 240 x 320;1 x 3 x 240 x 320
  • 参数量: 87 M
  • 计算量: 8.02 GFLOPs

Files In This Repo

  • ACT.zip (源模型 / 源模型下载; 源模型 / 源模型元数据)
  • act_distill_fp32_for_mindcmd_simp_release.om (编译模型 / OM 元数据 / a16w8)
  • SVP_NNN_PC_V1.0.6.0.tgz (附加资源 / 附加资源)

Upstream Links

Notes

  • This repository was mirrored from the HiSilicon Developer Portal model card and local downloads captured on 2026-03-27.
  • File ownership follows the portal card mapping, not just filename similarity.
  • Cover image: 1731868158459906_____.png
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