diff --git a/Toolformer-Language-Models-Can-Teach-Themselves-to-Use-Tools.html b/Toolformer-Language-Models-Can-Teach-Themselves-to-Use-Tools.html index d34cb91..ee172aa 100644 --- a/Toolformer-Language-Models-Can-Teach-Themselves-to-Use-Tools.html +++ b/Toolformer-Language-Models-Can-Teach-Themselves-to-Use-Tools.html @@ -200,7 +200,7 @@
Starting with a language model, M, the goal is to enable the language model to use tools by invoking API calls.
An API call is denoted by the tuple $c = (api-name, api-input)$. It can be linearized as $e(c) = [api-name(api-input)]$ or as $e(c, r) = [api-name(api-input) -> r]$ where $r$ denotes the result of the API.
+An API call is denoted by the tuple $c =$ (api_name, api_input). It can be linearized as $e(c) =$ [api_name(api_input)$]$ or as $e(c, r) = [$api_name(api_input) $ -> r]$ where $r$ denotes the result of the API.
The given dataset of plain text, $C$, is converted into a dataset $C*$ augmented with the API calls using a three-step process.
diff --git a/atom.xml b/atom.xml index a68100d..26ef666 100644 --- a/atom.xml +++ b/atom.xml @@ -4,7 +4,7 @@