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Pydantic model for training request validation. This version consolidates all model name and parameter logic into a single validator to prevent redundant operations and fix the duplicate suffix bug.
Dataset repository ID on Hugging Face, should be a public dataset
Type of model to train, supports 'ACT', 'gr00t', and 'pi0'
ACT
, ACT_BBOX
, gr00t
, pi0
, custom
Name of the trained model to upload to Hugging Face, should be in the format phospho-app/<model_name> or <model_name>
Whether to use private training (PRO users only)
Training parameters for the model. Training parameters are left to None by default and are set depending on the dataset in the training pipeline.
- TrainingParamsAct
- TrainingParamsActWithBbox
- TrainingParamsGr00T
- TrainingParamsPi0
User's personal HF token for private training
WandB API key for tracking training, you can find it at https://wandb.ai/authorize