model
superduper.ext.anthropic.model
AnthropicCompletions
​
AnthropicCompletions(self,
identifier: str,
db: dataclasses.InitVar[typing.Optional[ForwardRef('Datalayer')]] = None,
uuid: str = None,
*,
artifacts: 'dc.InitVar[t.Optional[t.Dict]]' = None,
signature: 'Signature' = '*args,
**kwargs',
datatype: 'EncoderArg' = None,
output_schema: 't.Optional[Schema]' = None,
flatten: 'bool' = False,
model_update_kwargs: 't.Dict' = None,
predict_kwargs: 't.Dict' = None,
compute_kwargs: 't.Dict' = None,
validation: 't.Optional[Validation]' = None,
metric_values: 't.Dict' = None,
model: 't.Optional[str]' = None,
max_batch_size: 'int' = 8,
client_kwargs: Dict[str,
Any] = None,
prompt: str = '') -> None
Parameter | Description |
---|---|
identifier | Identifier of the leaf. |
db | Datalayer instance. |
uuid | UUID of the leaf. |
artifacts | A dictionary of artifacts paths and DataType objects |
signature | Model signature. |
datatype | DataType instance. |
output_schema | Output schema (mapping of encoders). |
flatten | Flatten the model outputs. |
model_update_kwargs | The kwargs to use for model update. |
predict_kwargs | Additional arguments to use at prediction time. |
compute_kwargs | Kwargs used for compute backend job submit. Example (Ray backend): compute_kwargs = dict(resources=...). |
validation | The validation Dataset instances to use. |
metric_values | The metrics to evaluate on. |
model | The Model to use, e.g. 'text-embedding-ada-002' |
max_batch_size | Maximum batch size. |
client_kwargs | The keyword arguments to pass to the client. |
prompt | The prompt to use to seed the response. |
Cohere completions (chat) predictor.
Anthropic
​
Anthropic(self,
identifier: str,
db: dataclasses.InitVar[typing.Optional[ForwardRef('Datalayer')]] = None,
uuid: str = None,
*,
artifacts: 'dc.InitVar[t.Optional[t.Dict]]' = None,
signature: 'Signature' = '*args,
**kwargs',
datatype: 'EncoderArg' = None,
output_schema: 't.Optional[Schema]' = None,
flatten: 'bool' = False,
model_update_kwargs: 't.Dict' = None,
predict_kwargs: 't.Dict' = None,
compute_kwargs: 't.Dict' = None,
validation: 't.Optional[Validation]' = None,
metric_values: 't.Dict' = None,
model: 't.Optional[str]' = None,
max_batch_size: 'int' = 8,
client_kwargs: Dict[str,
Any] = None) -> None
Parameter | Description |
---|---|
identifier | Identifier of the leaf. |
db | Datalayer instance. |
uuid | UUID of the leaf. |
artifacts | A dictionary of artifacts paths and DataType objects |
signature | Model signature. |
datatype | DataType instance. |
output_schema | Output schema (mapping of encoders). |
flatten | Flatten the model outputs. |
model_update_kwargs | The kwargs to use for model update. |
predict_kwargs | Additional arguments to use at prediction time. |
compute_kwargs | Kwargs used for compute backend job submit. Example (Ray backend): compute_kwargs = dict(resources=...). |
validation | The validation Dataset instances to use. |
metric_values | The metrics to evaluate on. |
model | The Model to use, e.g. 'text-embedding-ada-002' |
max_batch_size | Maximum batch size. |
client_kwargs | The keyword arguments to pass to the client. |
Anthropic predictor.