ass_name": "DDPMScheduler",
  "_diffusers_version": "0.13.1",
  "beta_end": 0.02,
  "beta_schedule": "linear",
  "beta_start": 0.0001,
  "clip_sample": true,
  "clip_sample_range": 1.0,
  "num_train_timesteps": 1000,
  "prediction_type": "epsilon",
  "trained_betas": null,
  "variance_type": "fixed_small"
}
💡 Notice how the scheduler is instantiated from a configuration. Unlike a model, a scheduler does not have trainable weights and is paramet