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public static final class Generator.ModelParameter.Builder extends GeneratedMessageV3.Builder<Generator.ModelParameter.Builder> implements Generator.ModelParameterOrBuilderParameters to be passed to the LLM. If not set, default values will be used.
Protobuf type google.cloud.dialogflow.cx.v3beta1.Generator.ModelParameter
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > Generator.ModelParameter.BuilderImplements
Generator.ModelParameterOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public Generator.ModelParameter.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
build()
public Generator.ModelParameter build()| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter |
|
buildPartial()
public Generator.ModelParameter buildPartial()| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter |
|
clear()
public Generator.ModelParameter.Builder clear()| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
clearField(Descriptors.FieldDescriptor field)
public Generator.ModelParameter.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
clearMaxDecodeSteps()
public Generator.ModelParameter.Builder clearMaxDecodeSteps()The maximum number of tokens to generate.
optional int32 max_decode_steps = 2;
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public Generator.ModelParameter.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
clearTemperature()
public Generator.ModelParameter.Builder clearTemperature()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.
optional float temperature = 1;
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
clearTopK()
public Generator.ModelParameter.Builder clearTopK()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.
optional int32 top_k = 4;
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
clearTopP()
public Generator.ModelParameter.Builder clearTopP()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.
optional float top_p = 3;
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
clone()
public Generator.ModelParameter.Builder clone()| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
getDefaultInstanceForType()
public Generator.ModelParameter getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getMaxDecodeSteps()
public int getMaxDecodeSteps()The maximum number of tokens to generate.
optional int32 max_decode_steps = 2;
| Returns | |
|---|---|
| Type | Description |
int |
The maxDecodeSteps. |
getTemperature()
public float getTemperature()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.
optional float temperature = 1;
| Returns | |
|---|---|
| Type | Description |
float |
The temperature. |
getTopK()
public int getTopK()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.
optional int32 top_k = 4;
| Returns | |
|---|---|
| Type | Description |
int |
The topK. |
getTopP()
public float getTopP()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.
optional float top_p = 3;
| Returns | |
|---|---|
| Type | Description |
float |
The topP. |
hasMaxDecodeSteps()
public boolean hasMaxDecodeSteps()The maximum number of tokens to generate.
optional int32 max_decode_steps = 2;
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the maxDecodeSteps field is set. |
hasTemperature()
public boolean hasTemperature()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.
optional float temperature = 1;
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the temperature field is set. |
hasTopK()
public boolean hasTopK()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.
optional int32 top_k = 4;
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the topK field is set. |
hasTopP()
public boolean hasTopP()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.
optional float top_p = 3;
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the topP field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
mergeFrom(Generator.ModelParameter other)
public Generator.ModelParameter.Builder mergeFrom(Generator.ModelParameter other)| Parameter | |
|---|---|
| Name | Description |
other |
Generator.ModelParameter |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public Generator.ModelParameter.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public Generator.ModelParameter.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
mergeUnknownFields(UnknownFieldSet unknownFields)
public final Generator.ModelParameter.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
setField(Descriptors.FieldDescriptor field, Object value)
public Generator.ModelParameter.Builder setField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
setMaxDecodeSteps(int value)
public Generator.ModelParameter.Builder setMaxDecodeSteps(int value)The maximum number of tokens to generate.
optional int32 max_decode_steps = 2;
| Parameter | |
|---|---|
| Name | Description |
value |
intThe maxDecodeSteps to set. |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public Generator.ModelParameter.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
index |
int |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|
setTemperature(float value)
public Generator.ModelParameter.Builder setTemperature(float value)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.
optional float temperature = 1;
| Parameter | |
|---|---|
| Name | Description |
value |
floatThe temperature to set. |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
setTopK(int value)
public Generator.ModelParameter.Builder setTopK(int value)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.
optional int32 top_k = 4;
| Parameter | |
|---|---|
| Name | Description |
value |
intThe topK to set. |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
setTopP(float value)
public Generator.ModelParameter.Builder setTopP(float value)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.
optional float top_p = 3;
| Parameter | |
|---|---|
| Name | Description |
value |
floatThe topP to set. |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final Generator.ModelParameter.Builder setUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
Generator.ModelParameter.Builder |
|