# BeingBeyond/Being-H

Being-H is BeingBeyond's family of human-centric embodied foundation models.

Repository: https://github.com/BeingBeyond/Being-H
Canonical: https://ross.abutalabs.com/products/being-h
Homepage: https://research.beingbeyond.com/being-h08
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-08-25T05:05:42+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 29
- inputs: {"age_days": 412, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1126, forks 61 (observed 2026-08-28T04:03:41.245112+00:00)

## What it is
Being-H is a family of human-centric embodied foundation models, including VLA models (Being-H0.5, Being-H0) and latent world-action models (Being-H0.7, Being-H0.8) pretrained on large-scale egocentric human manipulation video. The repository provides training, inference, post-training, and deployment code plus pretrained checkpoints on Hugging Face for dexterous robot manipulation.

## Use cases
- train a vision-language-action model for dexterous robot hands
- pretrain a world-action model on egocentric human videos
- post-train a VLA model on a small amount of real robot data
- achieve cross-embodiment generalization for manipulation tasks
- generate tactile-aware contact predictions for grasping and insertion
- deploy pretrained manipulation models on humanoid robots or dexterous hands

## When to choose
- you need a human-video-pretrained VLA or world-action model for dexterous manipulation
- you want cross-embodiment transfer with minimal real-robot fine-tuning
- you are researching tactile or latent world models for embodied AI

## When to avoid
- you need a simple off-the-shelf robot control stack without model training
- your hardware lacks GPUs or the robotics setup the models target
- you need a mature production system rather than a research codebase

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, llm-training, simulation
- domain: robotics, machine-learning, artificial-intelligence, computer-vision
- platform: python
- tags: embodied-ai, vla, world-model, dexterous-manipulation, foundation-model, egocentric-video, tactile, humanoid-robotics, cross-embodiment, linux, gpu

## Member repositories
- BeingBeyond/Being-H (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:41.245112+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:39:10.874319+00:00, confidence not recorded.
  - readme: https://github.com/BeingBeyond/Being-H (fetched 2026-08-28T04:03:41.245112+00:00, sha 19efe69365b6)
  - homepage: https://research.beingbeyond.com/being-h08 (fetched 2026-08-29T12:43:47.811804+00:00, sha 8eae2c8ba395)
  - site_page: https://beingbeyond.com (fetched 2026-08-29T12:43:47.821793+00:00, sha ca0192c84685)
- Data as of 2026-08-30T08:39:29.467469+00:00.