From ffe777e519a223cea68e79485ceb2e1610f78b45 Mon Sep 17 00:00:00 2001
From: Meng Zhang <meng@tabbyml.com>
Date: Tue, 6 Jun 2023 19:53:40 -0700
Subject: [PATCH] docs: improve

---
 website/docs/self-hosting/01-docker.md  | 59 -------------------
 website/docs/self-hosting/01-docker.mdx | 76 +++++++++++++++++++++++++
 website/docs/self-hosting/02-apple.md   |  4 ++
 3 files changed, 80 insertions(+), 59 deletions(-)
 delete mode 100644 website/docs/self-hosting/01-docker.md
 create mode 100644 website/docs/self-hosting/01-docker.mdx

diff --git a/website/docs/self-hosting/01-docker.md b/website/docs/self-hosting/01-docker.md
deleted file mode 100644
index e84e958..0000000
--- a/website/docs/self-hosting/01-docker.md
+++ /dev/null
@@ -1,59 +0,0 @@
-# Docker
-
-There is a supplied docker image to make deploying a server as a container easier.
-
-
-## CPU
-
-**Command line**
-```bash
-docker run \
-  -p 8080:8080 -v $HOME/.tabby:/data \
-  tabbyml/tabby serve --model TabbyML/SantaCoder-1B
-```
-
-
-**Docker Compose**
-```yaml
-version: '3.5'
-
-services:
-  tabby:
-    restart: always
-    image: tabbyml/tabby
-    command: serve --model TabbyML/SantaCoder-1B
-    volumes:
-      - "$HOME/.tabby:/data"
-    ports:
-      - 8080:8080
-```
-
-## CUDA (requires NVIDIA Container Toolkit)
-
-**Command line**
-```bash
-docker run \
-  --gpus all -p 8080:8080 -v $HOME/.tabby:/data \
-  tabbyml/tabby \
-  serve --model TabbyML/SantaCoder-1B --device cuda
-```
-
-**Docker Compose**
-```yaml
-version: '3.5'
-services:
-  tabby:
-    restart: always
-    image: tabbyml/tabby
-    command: serve --model TabbyML/SantaCoder-1B --device cuda
-    volumes:
-      - "$HOME/.tabby:/data"
-    ports:
-      - 8080:8080
-    resources:
-    reservations:
-      devices:
-      - driver: nvidia
-        count: 1
-        capabilities: [gpu]
-```
diff --git a/website/docs/self-hosting/01-docker.mdx b/website/docs/self-hosting/01-docker.mdx
new file mode 100644
index 0000000..2a0e704
--- /dev/null
+++ b/website/docs/self-hosting/01-docker.mdx
@@ -0,0 +1,76 @@
+# Docker
+
+There is a supplied docker image to make deploying a server as a container easier.
+
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+## CPU
+
+<Tabs>
+  <TabItem value="shell" label="Shell" default>
+
+  ```bash title="run.sh"
+  docker run \
+    -p 8080:8080 -v $HOME/.tabby:/data \
+    tabbyml/tabby serve --model TabbyML/SantaCoder-1B
+  ```
+
+  </TabItem>
+  <TabItem value="compose" label="Docker Compose">
+
+```yaml title="docker-compose.yml"
+version: '3.5'
+
+services:
+  tabby:
+    restart: always
+    image: tabbyml/tabby
+    command: serve --model TabbyML/SantaCoder-1B
+    volumes:
+      - "$HOME/.tabby:/data"
+    ports:
+      - 8080:8080
+```
+
+  </TabItem>
+</Tabs>
+
+
+## CUDA (requires NVIDIA Container Toolkit)
+
+<Tabs>
+  <TabItem value="shell" label="Shell" default>
+
+  ```bash title="run.sh"
+  docker run \
+    --gpus all -p 8080:8080 -v $HOME/.tabby:/data \
+    tabbyml/tabby \
+    serve --model TabbyML/SantaCoder-1B --device cuda
+  ```
+
+  </TabItem>
+  <TabItem value="compose" label="Docker Compose">
+
+  ```yaml title="docker-compose.yml"
+  version: '3.5'
+  services:
+    tabby:
+      restart: always
+      image: tabbyml/tabby
+      command: serve --model TabbyML/SantaCoder-1B --device cuda
+      volumes:
+        - "$HOME/.tabby:/data"
+      ports:
+        - 8080:8080
+      resources:
+      reservations:
+        devices:
+        - driver: nvidia
+          count: 1
+          capabilities: [gpu]
+  ```
+
+  </TabItem>
+</Tabs>
+
diff --git a/website/docs/self-hosting/02-apple.md b/website/docs/self-hosting/02-apple.md
index d29672b..f08e002 100644
--- a/website/docs/self-hosting/02-apple.md
+++ b/website/docs/self-hosting/02-apple.md
@@ -7,3 +7,7 @@ Thanks to Apple's Accelerate and CoreML frameworks, we can now run Tabby on edge
 2. Run `tabby --help` to verify successful installation.
 
 3. Start the server with `tabby serve model --models TabbyML/T5P-220M`.
+
+
+:::tip
+The compute power of M1/M2 is limited and is likely to be sufficient only for individual usage. If you require a shared instance for a team, we recommend considering Docker hosting with CUDA. You can find more information about Docker [here](./docker).