From 2fa73a24248b33dbc521d448928854fbf53939ef Mon Sep 17 00:00:00 2001
From: Nan Xiao <me@nanx.me>
Date: Fri, 18 Oct 2024 20:02:59 -0400
Subject: [PATCH] Use readme as docs index

---
 README.md                         | 23 +++++++++++++++++++++--
 docs/index.md                     |  6 ++++++
 docs/scripts/{purl.sh => sync.sh} |  4 ++++
 3 files changed, 31 insertions(+), 2 deletions(-)
 rename docs/scripts/{purl.sh => sync.sh} (81%)

diff --git a/README.md b/README.md
index 5dac519..a6c51ab 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,25 @@
-# tinytopics
+# tinytopics <img src="assets/logo.png" align="right" width="120" />
 
-Fit topic models using neural Poisson non-negative matrix factorization with sum-to-one constraints.
+Topic modeling via sum-to-one constrained Poisson non-negative
+matrix factorization (NMF), built on PyTorch and runs on GPU.
+
+## Installation
+
+You can install tinytopics from PyPI:
+
+```bash
+pip install tinytopics
+```
+
+Or install the development version from GitHub:
+
+```bash
+git clone https://github.com/nanxstats/tinytopics.git
+cd tinytopics
+python3 -m pip install -e .
+```
+
+Try [getting started](articles/get-started.md).
 
 ## Known issues
 
diff --git a/docs/index.md b/docs/index.md
index b59c62d..a6c51ab 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -3,6 +3,8 @@
 Topic modeling via sum-to-one constrained Poisson non-negative
 matrix factorization (NMF), built on PyTorch and runs on GPU.
 
+## Installation
+
 You can install tinytopics from PyPI:
 
 ```bash
@@ -18,3 +20,7 @@ python3 -m pip install -e .
 ```
 
 Try [getting started](articles/get-started.md).
+
+## Known issues
+
+- [ ] Running on CPU produces different (and worse) models than on GPU.
diff --git a/docs/scripts/purl.sh b/docs/scripts/sync.sh
similarity index 81%
rename from docs/scripts/purl.sh
rename to docs/scripts/sync.sh
index c0524be..a2ee1d4 100644
--- a/docs/scripts/purl.sh
+++ b/docs/scripts/sync.sh
@@ -1,5 +1,9 @@
 #!/bin/bash
 
+# Sync README.md
+cp README.md docs/index.md
+
+# Sync articles
 quarto render docs/articles/get-started.qmd
 quarto convert docs/articles/get-started.qmd
 jupyter nbconvert --to python docs/articles/get-started.ipynb --output ../../examples/get-started.py