From 7dbaef3f5b854babb656141596e548227f6ec41f Mon Sep 17 00:00:00 2001
From: Omar Sanseviero <osanseviero@gmail.com>
Date: Thu, 10 Aug 2023 14:32:51 +0200
Subject: [PATCH] Minor docs style fixes (#806)

---
 docs/source/basic_tutorials/consuming_tgi.md |  5 ++---
 docs/source/installation.md                  | 15 ++++++++-------
 docs/source/quicktour.md                     |  4 ++--
 3 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/docs/source/basic_tutorials/consuming_tgi.md b/docs/source/basic_tutorials/consuming_tgi.md
index 619e0a31f..7fb74719f 100644
--- a/docs/source/basic_tutorials/consuming_tgi.md
+++ b/docs/source/basic_tutorials/consuming_tgi.md
@@ -6,7 +6,7 @@ There are many ways you can consume Text Generation Inference server in your app
 
 After the launch, you can query the model using either the `/generate` or `/generate_stream` routes:
 
-```shell
+```bash
 curl 127.0.0.1:8080/generate \
     -X POST \
     -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
@@ -20,14 +20,13 @@ curl 127.0.0.1:8080/generate \
 
 You can simply install `huggingface-hub` package with pip.
 
-```python
+```bash
 pip install huggingface-hub
 ```
 
 Once you start the TGI server, instantiate `InferenceClient()` with the URL to the endpoint serving the model. You can then call `text_generation()` to hit the endpoint through Python. 
 
 ```python
-
 from huggingface_hub import InferenceClient
 
 client = InferenceClient(model=URL_TO_ENDPOINT_SERVING_TGI)
diff --git a/docs/source/installation.md b/docs/source/installation.md
index 4105acf43..a8e2e7516 100644
--- a/docs/source/installation.md
+++ b/docs/source/installation.md
@@ -16,7 +16,7 @@ Text Generation Inference is available on pypi, conda and GitHub.
 To install and launch locally, first [install Rust](https://rustup.rs/) and create a Python virtual environment with at least
 Python 3.9, e.g. using conda:
 
-```shell
+```bash
 curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
 
 conda create -n text-generation-inference python=3.9
@@ -27,7 +27,7 @@ You may also need to install Protoc.
 
 On Linux:
 
-```shell
+```bash
 PROTOC_ZIP=protoc-21.12-linux-x86_64.zip
 curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP
 sudo unzip -o $PROTOC_ZIP -d /usr/local bin/protoc
@@ -37,13 +37,13 @@ rm -f $PROTOC_ZIP
 
 On MacOS, using Homebrew:
 
-```shell
+```bash
 brew install protobuf
 ```
 
 Then run to install Text Generation Inference:
 
-```shell
+```bash
 BUILD_EXTENSIONS=True make install # Install repository and HF/transformer fork with CUDA kernels
 ```
 
@@ -51,7 +51,7 @@ BUILD_EXTENSIONS=True make install # Install repository and HF/transformer fork
 
 On some machines, you may also need the OpenSSL libraries and gcc. On Linux machines, run:
 
-```shell
+```bash
 sudo apt-get install libssl-dev gcc -y
 ```
 
@@ -59,13 +59,14 @@ sudo apt-get install libssl-dev gcc -y
 
 Once installation is done, simply run:
 
-```shell
+```bash
 make run-falcon-7b-instruct
 ```
 
 This will serve Falcon 7B Instruct model from the port 8080, which we can query.
 
 To see all options to serve your models, check in the [codebase](https://github.com/huggingface/text-generation-inference/blob/main/launcher/src/main.rs) or the CLI:
-```
+
+```bash
 text-generation-launcher --help
 ```
diff --git a/docs/source/quicktour.md b/docs/source/quicktour.md
index 31185a2d3..77f0a9c52 100644
--- a/docs/source/quicktour.md
+++ b/docs/source/quicktour.md
@@ -19,7 +19,7 @@ To use GPUs, you need to install the [NVIDIA Container Toolkit](https://docs.nvi
 
 Once TGI is running, you can use the `generate` endpoint by doing requests. To learn more about how to query the endpoints, check the [Consuming TGI](./basic_tutorials/consuming_tgi) section.
 
-```shell
+```bash
 curl 127.0.0.1:8080/generate -X POST -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' -H 'Content-Type: application/json'
 ```
 
@@ -27,7 +27,7 @@ curl 127.0.0.1:8080/generate -X POST -d '{"inputs":"What is Deep Learning?","par
 
 To see all possible flags and options, you can use the `--help` flag. It's possible to configure the number of shards, quantization, generation parameters, and more.
 
-```shell
+```bash
 docker run ghcr.io/huggingface/text-generation-inference:1.0.0 --help
 ```