Vllm.Outputs.ClassificationOutput (VLLM v0.3.0)

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The output data of one classification output of a request.

Parameters

  • probs - The probability vector, which is a list of floats. Its length depends on the number of classes.

Summary

Types

t()

Functions

from_base(ref, pooling_output, opts \\ [])

Python method ClassificationOutput.from_base.

new(probs, opts \\ [])

Initialize self. See help(type(self)) for accurate signature.

num_classes(ref)

Types

t()

@opaque t()

Functions

from_base(ref, pooling_output, opts \\ [])

@spec from_base(SnakeBridge.Ref.t(), Vllm.Outputs.PoolingOutput.t(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

Python method ClassificationOutput.from_base.

Parameters

  • pooling_output (Vllm.Outputs.PoolingOutput.t())

Returns

  • term()

new(probs, opts \\ [])

@spec new(
  [float()],
  keyword()
) :: {:ok, SnakeBridge.Ref.t()} | {:error, Snakepit.Error.t()}

Initialize self. See help(type(self)) for accurate signature.

Parameters

  • probs (list(float()))

num_classes(ref)

@spec num_classes(SnakeBridge.Ref.t()) :: {:ok, term()} | {:error, Snakepit.Error.t()}