IInferenceParams
Namespace: LLama.Abstractions
The parameters used for inference.
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Properties
TokensKeep
number of tokens to keep from initial prompt
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Property Value
MaxTokens
how many new tokens to predict (n_predict), set to -1 to inifinitely generate response until it complete.
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Property Value
LogitBias
logit bias for specific tokens
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Property Value
Dictionary<LLamaToken, Single>
AntiPrompts
Sequences where the model will stop generating further tokens.
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Property Value
TopK
0 or lower to use vocab size
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Property Value
TopP
1.0 = disabled
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Property Value
MinP
0.0 = disabled
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Property Value
TfsZ
1.0 = disabled
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Property Value
TypicalP
1.0 = disabled
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Property Value
Temperature
1.0 = disabled
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Property Value
RepeatPenalty
1.0 = disabled
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Property Value
RepeatLastTokensCount
last n tokens to penalize (0 = disable penalty, -1 = context size) (repeat_last_n)
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Property Value
FrequencyPenalty
frequency penalty coefficient 0.0 = disabled
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Property Value
PresencePenalty
presence penalty coefficient 0.0 = disabled
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Property Value
Mirostat
Mirostat uses tokens instead of words. algorithm described in the paper https://arxiv.org/abs/2007.14966. 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
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Property Value
MirostatTau
target entropy
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Property Value
MirostatEta
learning rate
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Property Value
PenalizeNL
consider newlines as a repeatable token (penalize_nl)
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Property Value
Grammar
Grammar to constrain possible tokens
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Property Value
SamplingPipeline
Set a custom sampling pipeline to use. If this is set All other sampling parameters are ignored!
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