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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].
  • TensorFlow [~generation.TFGenerationMixin.generate] is implemented in [~generation.TFGenerationMixin].
  • Flax/JAX [~generation.FlaxGenerationMixin.generate] is implemented in [~generation.FlaxGenerationMixin].

Regardless of your framework of choice, 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. 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

[[autodoc]] generation.WatermarkingConfig

GenerationMixin

[[autodoc]] generation.GenerationMixin - generate - compute_transition_scores

TFGenerationMixin

[[autodoc]] generation.TFGenerationMixin - generate - compute_transition_scores

FlaxGenerationMixin

[[autodoc]] generation.FlaxGenerationMixin - generate