Action Chunking with Transformers (ACT) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates. This policy has been trained and pushed to the Hub using LeRobot. Learn how to train and run it in the LeRobot act guide, or browse the full documentation. The policy consumes these observation features and produces these action features. Inputs Outputs New to LeRobot? These guides cover the full workflow: - Install LeRobot — set up the lerobot package. - Hardware setup — assemble, wire, and calibrate your robot and cameras. - Record data & train a policy — the end-to-end imitation-learning…
omx_item_b_100ep_act_150k is an open-weight model for robotics from Jeon. It has 52M parameters. At 16-bit it needs about 0.1 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
ACT policy trained on 100 demonstration episodes. Selected checkpoint: 150,000 training steps. Matching hardware calibration and custom LeRobot code are required. Keep all processor JSON and normalization safetensors files together with the model weights.
Parameters52M
Context—
Weights206.7 MB
License—
AccessOpen weights
Monthly Downloads—
Runs On
What it takes to serve omx_item_b_100ep_act_150k (52M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 0.1 GB | 0.1 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.1 GB | 0.1 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 19, 2026.
omx_item_b_100ep_act_150k on every accelerator the SAVRN Index prices, at every precision
Model Card
ACT policy trained on 100 demonstration episodes. Selected checkpoint: 150,000 training steps. Matching hardware calibration and custom LeRobot code are required. Keep all processor JSON and normalization safetensors files together with the model weights. Source run: warehouseitemb100mergedact200k. Selected through operator tests; no standardized success rate is claimed. Deployment code: https://github.com/E1I6-Logistics/OMX (access may be required). Base PC source: LeRobot 0.6.2, commit 89236ea0f4f81a81ca566081e20dd1ff5f823cbe plus custom modifications.
Excerpt from the card by Jeon.
Identity and Version
- Repository
- Jeonminjun/omx_item_b_100ep_act_150k
- Publisher
- Jeon
- Task
- Robotics
- Modality
- Control
- Library
- lerobot
- Parameters
- 52M parameters
- Languages
- act, omx
- Revision
- 08f468e1d690e7ff7775c3dc2eb30d51d83134c6
- First published
- 2026-10-01
- Last updated
- 2026-10-01
Files and Weights
9 files, 206.7 MB in total. The weights are 3 files totalling 206.7 MB in safetensors.
Weights3 files · 206.7 MB
Configuration4 files · 11.3 KB
Documentation1 file · 770 B
Repository1 file · 1.5 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 206.7 MB | 514c42db5fac |
| policy_postprocessor_step_0_unnormalizer_processor.safetensors | Weights | 7.6 KB | 16996082d7fb |
| policy_preprocessor_step_3_normalizer_processor.safetensors | Weights | 7.6 KB | b9e039c21797 |
| config.json | Configuration | 1.7 KB | — |
| policy_postprocessor.json | Configuration | 660 B | — |
| policy_preprocessor.json | Configuration | 1.3 KB | — |
| train_config.json | Configuration | 7.6 KB | — |
| README.md | Documentation | 770 B | — |
| .gitattributes | Repository | 1.5 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 206.7 MB
Download from Jeon
Released by Jeon through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 206.7 MB |
| 16-bit | 0.1 GB |
| 8-bit | 0.1 GB |
| 4-bit | 0.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About omx_item_b_100ep_act_150k
How much GPU memory does omx_item_b_100ep_act_150k need?
About 0.1 GB at 16-bit and 0 GB at 4-bit: the weights (52M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run omx_item_b_100ep_act_150k on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Similar Models
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