vibecodemaster/white-lid-smolvla

robotics model by vibecodemaster

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Robot policy trained to move the white lid onto the black tray. This branch contains 4,000 optimizer steps. The default branch contains 4,000 steps; step count alone does not establish better robot performance. The 4k checkpoint was reported by the operator to reach the lid in some trials. Gripper closure and repeatability remain unreliable. No standardized physical success evaluation or success-rate denominator has been collected. These are experimental checkpoints. Each branch is a complete loadable checkpoint including model weights, pre/postprocessing configuration, and normalization statistics. The tokenizer is included. Two RGB views, observation.images.camera0 and observation.images.camera1, each shaped 3 × 224 × 398 with pixels in [0, 1], and an eight-component observation.state. Joint order is motor1.pos through motor8.pos. The first seven joint positions use calibrated [-100, 100] units; the final gripper dimension uses calibrated [0, 100]. Actions are absolute follower goals in that same order and calibration, not deltas or radians. Action…

vibecodemaster/white-lid-smolvla on Hugging Face A short preview, not the full document.

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  1. White-lid SmolVLA
  2. Checkpoints
  3. Training provenance
  4. Inputs and outputs
  5. Loading
  6. Evaluation artifacts
  7. Packaging

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Model overview

vibecodemaster/white-lid-smolvla is a robotics model repository published by vibecodemaster on Hugging Face. The source reports the lerobot library.

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

Model facts

Task
robotics
Library
lerobot
Recent downloads (30 days)
0
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
450,046,176
Architecture
Not reported
License
Not reported — check the model card
Access
Not gated by Hugging Face
Created
2026-10-18T06:06:46.000Z
Last modified
2026-10-18T06:07:30.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: lerobot/smolvla_base

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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Source: Hugging Face Hub. Metadata observed 2026-10-18T06:43:02.030Z. Daily imports are snapshots, not real-time monitoring.

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