save(file_path: Union[pathlib.Path, str]) → None#
Save the LLM.
Parameters
file_path – Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=”path/llm.yaml”)
classmethod update_forward_refs(**localns: Any) → None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
property lc_attributes: Dict#
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]#
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]#
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool#
Return whether or not the class is serializable.
pydantic model langchain.llms.Replicate[source]#
Wrapper around Replicate models.
To use, you should have the replicate python package installed,
and the environment variable REPLICATE_API_TOKEN set with your API token.
You can find your token here: https://replicate.com/account
The model param is required, but any other model parameters can also
be passed in with the format input={model_param: value, …}
Example
from langchain.llms import Replicate
replicate = Replicate(model="stability-ai/stable-diffusion:                                          27b93a2413e7f36cd83da926f365628                                         0b2931564ff050bf9575f1fdf9bcd7478",
                      input={"image_dimensions": "512x512"})
Validators
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html