adjust toctree and shell to bash

docs/source/_toctree.yml

@@ -16,5 +16,5 @@
   - local: basic_tutorials/gated_model_access
     title: Serving Private & Gated Models
   - local: basic_tutorials/using_cli
-    title: Using TGI through CLI
+    title: Using TGI CLI
   title: Tutorials

docs/source/basic_tutorials/using_cli.md

@@ -30,6 +30,6 @@ You can also find it hosted in this [Swagger UI](https://huggingface.github.io/t
 
 Same documentation can be found for `text-generation-server`.
 
-```shell
+```bash
 text-generation-server --help
 ```

docs/source/installation.md

@@ -8,14 +8,14 @@ You can use TGI command-line interface (CLI) to download weights, serve and quan
 
 To install the CLI, you need to first clone the TGI repository and then run `make`.
 
-```shell
+```bash
 git clone https://github.com/huggingface/text-generation-inference.git && cd text-generation-inference
 make install
 ```
 
 If you would like to serve models with custom kernels, run
 
-```shell
+```bash
 BUILD_EXTENSIONS=True make install
 ```
 
@@ -28,7 +28,7 @@ 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
@@ -39,7 +39,7 @@ 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
@@ -49,13 +49,13 @@ rm -f $PROTOC_ZIP
 
 On MacOS, using Homebrew:
 
-```shell
+```bash
 brew install protobuf
 ```
 
 Then run to install Text Generation Inference:
 
-```shell
+```bash
 git clone https://github.com/huggingface/text-generation-inference.git && cd text-generation-inference
 BUILD_EXTENSIONS=True make install
 ```
@@ -64,7 +64,7 @@ BUILD_EXTENSIONS=True make install
 
 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
 ```
 
@@ -72,7 +72,7 @@ sudo apt-get install libssl-dev gcc -y
 
 Once installation is done, simply run:
 
-```shell
+```bash
 make run-falcon-7b-instruct
 ```
 

docs/source/quicktour.md

@@ -4,7 +4,7 @@ The easiest way of getting started is using the official Docker container. Insta
 
 Let's say you want to deploy [Falcon-7B Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct) model with TGI. Here is an example on how to do that:
 
-```shell
+```bash
 model=tiiuae/falcon-7b-instruct
 volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run
 
@@ -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
 ```