TopKSampler
TopKSampler class
keras_nlp.samplers.TopKSampler(k=5, seed=None, **kwargs)
Top-K Sampler class.
This sampler implements top-k search algorithm. Briefly, top-k algorithm randomly selects a token from the tokens of top K probability, with selection chance determined by the probability.
Arguments
- k: int, the
kvalue of top-k. - seed: int. The random seed. Defaults to
None.
Call arguments
{{call_args}}
Examples
causal_lm = keras_nlp.models.GPT2CausalLM.from_preset("gpt2_base_en")
# Pass by name to compile.
causal_lm.compile(sampler="top_k")
causal_lm.generate(["Keras is a"])
# Pass by object to compile.
sampler = keras_nlp.samplers.TopKSampler(k=5, temperature=0.7)
causal_lm.compile(sampler=sampler)
causal_lm.generate(["Keras is a"])