Start training an ACT or gr00t model on the specified dataset. This will upload a trained model to the Hugging Face Hub using the main branch of the specified dataset.
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.
User's personal HF token for private training
WandB API key for tracking training, you can find it at https://wandb.ai/authorize