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| # Generation | |
| Each framework has a generate method for text generation implemented in their respective `GenerationMixin` class: | |
| - PyTorch [`~generation.GenerationMixin.generate`] is implemented in [`~generation.GenerationMixin`]. | |
| You can parameterize the generate method with a [`~generation.GenerationConfig`] class instance. Please refer to this class for the complete list of generation parameters, which control the behavior of the generation method. | |
| To learn how to inspect a model's generation configuration, what are the defaults, how to change the parameters ad hoc, | |
| and how to create and save a customized generation configuration, refer to the | |
| [text generation strategies guide](../generation_strategies). The guide also explains how to use related features, | |
| like token streaming. | |
| ## GenerationConfig | |
| [[autodoc]] generation.GenerationConfig | |
| - from_pretrained | |
| - from_model_config | |
| - save_pretrained | |
| - update | |
| - validate | |
| - get_generation_mode | |
| ## GenerationMixin | |
| [[autodoc]] GenerationMixin | |
| - generate | |
| - compute_transition_scores | |
| ## ContinuousMixin | |
| [[autodoc]] generation.ContinuousMixin | |
| ## ContinuousBatchingManager | |
| [[autodoc]] generation.ContinuousBatchingManager | |
| ## Scheduler | |
| [[autodoc]] generation.Scheduler | |
| ## FIFOScheduler | |
| [[autodoc]] generation.FIFOScheduler | |
| ## PrefillFirstScheduler | |
| [[autodoc]] generation.PrefillFirstScheduler | |