Reference documentation and code samples for the Dialogflow CX V3 API class Google::Cloud::Dialogflow::CX::V3::Generator::ModelParameter.
Parameters to be passed to the LLM. If not set, default values will be used.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#max_decode_steps
def max_decode_steps() -> ::Integer
Returns
- (::Integer) — The maximum number of tokens to generate.
#max_decode_steps=
def max_decode_steps=(value) -> ::Integer
Parameter
- value (::Integer) — The maximum number of tokens to generate.
Returns
- (::Integer) — The maximum number of tokens to generate.
#temperature
def temperature() -> ::Float
Returns
- (::Float) — The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
#temperature=
def temperature=(value) -> ::Float
Parameter
- value (::Float) — The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
Returns
- (::Float) — The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
#top_k
def top_k() -> ::Integer
Returns
- (::Integer) — If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
#top_k=
def top_k=(value) -> ::Integer
Parameter
- value (::Integer) — If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
Returns
- (::Integer) — If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
#top_p
def top_p() -> ::Float
Returns
- (::Float) — If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
#top_p=
def top_p=(value) -> ::Float
Parameter
- value (::Float) — If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
Returns
- (::Float) — If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.