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Currently it's not super easy to fine-tune pretrained policies due to several limitations in the configs design. We're addressing this in #550 and we'll keep improving usability afterwards.
In the meantime, you can have a look at examples/2_evaluate_pretrained_policy.py to get an idea of how to use (in eval) a pretrained policy but keep in mind it's going to obsolete very soon. Our pretrained policies are available on https://huggingface.co/lerobot but we'll have to retrain them with the current redesign.
Are there any pretrained models available that can be fine tuned using our own dataset for tasks like pick and place and manipulation?
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