@@ -8,7 +8,7 @@ section below.
88
99## Requirements
1010
11- - Supported operating systems: Linux, Mac
11+ - Linux or macOS
1212- [ OCaml 4.07.1] ( https://ocaml.org )
1313- [ SerAPI 0.7.1] ( https://github.com/ejgallego/coq-serapi )
1414- [ Coq 8.10.2] ( https://coq.inria.fr/download )
@@ -84,25 +84,7 @@ conda activate roosterize
8484
8585### Installation of Roosterize and trained models
8686
87- Next, you need to obtain pre-trained models that capture
88- naming conventions. We have trained several models using our
89- [ corpus] [ math-comp-corpus ] , which follows the conventions
90- used in the [ Mathematical Components] [ math-comp-website ]
91- family of projects. These models are available for separate
92- [ download] [ models-link ] .
93-
94- To use our pre-trained models, go to the Roosterize
95- root directory, and download and unpack the archive (` models.tgz ` ):
96- ```
97- wget https://github.com/EngineeringSoftware/roosterize/releases/download/v8.10.0/models.tgz
98- tar xzf models.tgz
99- ```
100-
101- [ models-link ] : https://github.com/EngineeringSoftware/roosterize/releases/download/v8.10.0/models.tgz
102-
103- ## Usage
104-
105- You need to obtain a pre-trained model that capture naming
87+ Next, you need to obtain a pre-trained model that capture naming
10688conventions. The default pre-trained model, which was trained using
10789our [ corpus] [ math-comp-corpus ] and follows the conventions used in the
10890[ Mathematical Components] [ math-comp-website ] family of projects, can
@@ -116,6 +98,8 @@ The model will be downloaded to `$HOME/.roosterize/`. To use a
11698different model (that we [ released] [ latest-release ] or you trained),
11799simply put it in ` $HOME/.roosterize/ ` .
118100
101+ ## Usage
102+
119103To use Roosterize on a Coq verification project, you first need to
120104build the Coq project using a command provided by the project (usually
121105` make ` ). Then, run this command to get the lemma name suggestions for
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