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* Rename index.mdx to index.md * With saved modifs * Address review comment * Treat all files * .mdx -> .md * Remove special char * Update utils/tests_fetcher.py Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr> --------- Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
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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
GenerationMixin
autodoc generation.GenerationMixin - generate - compute_transition_scores - greedy_search - sample - beam_search - beam_sample - contrastive_search - group_beam_search - constrained_beam_search
TFGenerationMixin
autodoc generation.TFGenerationMixin - generate - compute_transition_scores
FlaxGenerationMixin
autodoc generation.FlaxGenerationMixin - generate