GnanaPraveen/Bagel-Robotics-1-Public

robotics model by GnanaPraveen

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Model card & documentation

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Approved public mirror of the exact checkpoint 1000 from bageldotcom/Bagel-Robotics-1, used in the Bagel-Robotics-1 evaluation campaign. This mirror is public and its files can be downloaded without a token. The original organization repository remains private. This is distinct from Bagel-Robotics-1-Preview. The video expert has 12,468,409,664 parameters, 23.95% fewer than its recorded parent. Learned masks were converted into smaller FFN and cross-attention layers. Self-attention heads and the action expert are retained. No teacher or learned-mask module is required for inference. Parameter reduction is not a measured inference-speedup claim. The release adds documentation and inference packaging without changing any checkpoint file. The original checkpoint revision and file hashes are retained as provenance. Hugging Face duplication created a new mirror commit; consult the source repository for its full branch and tag history. Current release files focus on inference. COMPLETE.json is the original export receipt, including export-time paths and simulationcompleted: false; it is retained…

GnanaPraveen/Bagel-Robotics-1-Public on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-11-07T07:47:32.772Z

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Model overview

GnanaPraveen/Bagel-Robotics-1-Public is a robotics model repository published by GnanaPraveen on Hugging Face. A library was not reported.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task: robotics
Library: Not reported
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: Not reported
Architecture: Not reported
License: Not reported — check the model card
Access: Not gated by Hugging Face
Created: 2026-11-07T06:39:24.000Z
Last modified: 2026-11-07T06:44:12.000Z

Compatibility and lineage

Reported languages: en

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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