"steps_offset": 0,
"thresholding": false,
"timestep_spacing": "leading",
"trained_betas": null,
"variance_type": "fixed_small"
}
```  
<Tip>  
💡 Unlike a model, a scheduler does not have trainable weights and is parameter-free!  
</Tip>  
Some of the most important parameters are:  
* `num_train_timesteps`: the length of the denoising process or, in other words, the number of timesteps required to process random Gaussian noise into a data sample.