Instructions to use epronovost/trajectory-classifier-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use epronovost/trajectory-classifier-model with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +1 -1
- model.safetensors +1 -1
- train_config.json +2 -2
README.md
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model_name: reward_classifier
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pipeline_tag: robotics
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tags:
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- reward_classifier
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- robotics
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---
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model_name: reward_classifier
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pipeline_tag: robotics
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tags:
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- reward_classifier
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- lerobot
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- robotics
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---
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 24357828
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version https://git-lfs.github.com/spec/v1
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oid sha256:2eeaf4d276253fbff85dd86205bf1baca97c949cb73efec7e5a2f1a0fd43f467
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size 24357828
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train_config.json
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"VISUAL": "MEAN_STD"
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}
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},
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"output_dir": "outputs/train/2026-03-12/16-
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"job_name": "reward-classifier",
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"resume": false,
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"seed": 2,
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"project": "reward-classifier",
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"entity": null,
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"notes": null,
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"run_id": "
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"mode": null,
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"add_tags": true
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},
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"VISUAL": "MEAN_STD"
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}
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},
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"output_dir": "outputs/train/2026-03-12/16-23-03_reward-classifier",
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"job_name": "reward-classifier",
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"resume": false,
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"seed": 2,
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"project": "reward-classifier",
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"entity": null,
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"notes": null,
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"run_id": "gtorx0s8",
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"mode": null,
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"add_tags": true
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},
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