@ -10,7 +10,7 @@ but potentially an unknown chain that depends on the user's input.
In these types of chains, there is a “agent” which has access to a suite of tools.
Depending on the user input, the agent can then decide which, if any, of these tools to call.
In this section of documentation, we first start with a Getting Started notebook to over over how to use all things related to agents in an end-to-end manner.
In this section of documentation, we first start with a Getting Started notebook to cover how to use all things related to agents in an end-to-end manner.
"First, lets go over loading a LLM from disk. LLMs can be saved on disk in two formats: json or yaml. No matter the extension, they are loaded in the same way."
"First, lets go over loading an LLM from disk. LLMs can be saved on disk in two formats: json or yaml. No matter the extension, they are loaded in the same way."
]
},
{
@ -112,7 +112,7 @@
"metadata": {},
"source": [
"## Saving\n",
"If you want to go from a LLM in memory to a serialized version of it, you can do so easily by calling the `.save` method. Again, this supports both json and yaml."
"If you want to go from an LLM in memory to a serialized version of it, you can do so easily by calling the `.save` method. Again, this supports both json and yaml."