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# Octo Base
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This model is trained with a window size of 2, predicting 7-dimensional actions 4 steps into the future using a diffusion policy.
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Observations and tasks conform to the following spec:
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Observations:
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# Octo Base
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This model is trained with a window size of 2, predicting 7-dimensional actions 4 steps into the future using a diffusion policy. The model is a Transformer with 93M parameters (equivalent to a ViT-B). Images are tokenized by preprocessing with a lightweight convolutional encoder, then grouped into 16x16 patches. Language is tokenized by applying the T5 tokenizer, and then applying the T5-Base language encoder.
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Observations and tasks conform to the following spec:
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Observations:
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