Preparing for release. (#2285)

* Preparing for release.

* Updating docs.

* Fixing token within the docker image for the launcher.

Cargo.lock

@@ -3762,7 +3762,7 @@ dependencies = [
 
 [[package]]
 name = "text-generation-benchmark"
-version = "2.1.2-dev0"
+version = "2.2.1-dev0"
 dependencies = [
  "average",
  "clap",
@@ -3783,7 +3783,7 @@ dependencies = [
 
 [[package]]
 name = "text-generation-client"
-version = "2.1.2-dev0"
+version = "2.2.1-dev0"
 dependencies = [
  "async-trait",
  "base64 0.22.1",
@@ -3801,7 +3801,7 @@ dependencies = [
 
 [[package]]
 name = "text-generation-launcher"
-version = "2.1.2-dev0"
+version = "2.2.1-dev0"
 dependencies = [
  "clap",
  "ctrlc",
@@ -3820,7 +3820,7 @@ dependencies = [
 
 [[package]]
 name = "text-generation-router"
-version = "2.1.2-dev0"
+version = "2.2.1-dev0"
 dependencies = [
  "async-stream",
  "axum 0.7.5",

Cargo.toml

@@ -9,7 +9,7 @@ members = [
 resolver = "2"
 
 [workspace.package]
-version = "2.1.2-dev0"
+version = "2.2.1-dev0"
 edition = "2021"
 authors = ["Olivier Dehaene"]
 homepage = "https://github.com/huggingface/text-generation-inference"

README.md

@@ -80,7 +80,7 @@ model=HuggingFaceH4/zephyr-7b-beta
 volume=$PWD/data
 
 docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data \
-    ghcr.io/huggingface/text-generation-inference:2.1.1 --model-id $model
+    ghcr.io/huggingface/text-generation-inference:2.2.0 --model-id $model
 ```
 
 And then you can make requests like
@@ -94,7 +94,7 @@ curl 127.0.0.1:8080/generate_stream \
 
 **Note:** To use NVIDIA GPUs, you need to install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html). We also recommend using NVIDIA drivers with CUDA version 12.2 or higher. For running the Docker container on a machine with no GPUs or CUDA support, it is enough to remove the `--gpus all` flag and add `--disable-custom-kernels`, please note CPU is not the intended platform for this project, so performance might be subpar.
 
-**Note:** TGI supports AMD Instinct MI210 and MI250 GPUs. Details can be found in the [Supported Hardware documentation](https://huggingface.co/docs/text-generation-inference/supported_models#supported-hardware). To use AMD GPUs, please use `docker run --device /dev/kfd --device /dev/dri --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:2.1.1-rocm --model-id $model` instead of the command above.
+**Note:** TGI supports AMD Instinct MI210 and MI250 GPUs. Details can be found in the [Supported Hardware documentation](https://huggingface.co/docs/text-generation-inference/supported_models#supported-hardware). To use AMD GPUs, please use `docker run --device /dev/kfd --device /dev/dri --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:2.2.0-rocm --model-id $model` instead of the command above.
 
 To see all options to serve your models (in the [code](https://github.com/huggingface/text-generation-inference/blob/main/launcher/src/main.rs) or in the cli):
 ```

docs/openapi.json

@@ -10,7 +10,7 @@
       "name": "Apache 2.0",
       "url": "https://www.apache.org/licenses/LICENSE-2.0"
     },
-    "version": "2.1.2-dev0"
+    "version": "2.2.1-dev0"
   },
   "paths": {
     "/": {

docs/source/installation_amd.md

@@ -11,7 +11,7 @@ volume=$PWD/data # share a volume with the Docker container to avoid downloading
 docker run --rm -it --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
     --device=/dev/kfd --device=/dev/dri --group-add video \
     --ipc=host --shm-size 256g --net host -v $volume:/data \
-    ghcr.io/huggingface/text-generation-inference:2.1.1-rocm \
+    ghcr.io/huggingface/text-generation-inference:2.2.0-rocm \
     --model-id $model
 ```
 

docs/source/installation_intel.md

@@ -12,7 +12,7 @@ volume=$PWD/data # share a volume with the Docker container to avoid downloading
 docker run --rm --privileged --cap-add=sys_nice \
     --device=/dev/dri \
     --ipc=host --shm-size 1g --net host -v $volume:/data \
-    ghcr.io/huggingface/text-generation-inference:latest-intel \
+    ghcr.io/huggingface/text-generation-inference:2.2.0-intel \
     --model-id $model --cuda-graphs 0
 ```
 

docs/source/installation_nvidia.md

@@ -11,7 +11,7 @@ model=teknium/OpenHermes-2.5-Mistral-7B
 volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run
 
 docker run --gpus all --shm-size 64g -p 8080:80 -v $volume:/data \
-    ghcr.io/huggingface/text-generation-inference:2.1.1 \
+    ghcr.io/huggingface/text-generation-inference:2.2.0 \
     --model-id $model
 ```
 

docs/source/quicktour.md

@@ -11,7 +11,7 @@ model=teknium/OpenHermes-2.5-Mistral-7B
 volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run
 
 docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data \
-    ghcr.io/huggingface/text-generation-inference:2.1.1 \
+    ghcr.io/huggingface/text-generation-inference:2.2.0 \
     --model-id $model
 ```
 
@@ -88,7 +88,7 @@ curl 127.0.0.1:8080/generate \
 To see all possible deploy flags and options, you can use the `--help` flag. It's possible to configure the number of shards, quantization, generation parameters, and more.
 
 ```bash
-docker run ghcr.io/huggingface/text-generation-inference:2.1.1 --help
+docker run ghcr.io/huggingface/text-generation-inference:2.2.0 --help
 ```
 
 </Tip>

launcher/src/main.rs

 use clap::{Parser, ValueEnum};
-use hf_hub::{api::sync::Api, Repo, RepoType};
+use hf_hub::{
+    api::sync::{Api, ApiBuilder},
+    Repo, RepoType,
+};
 use nix::sys::signal::{self, Signal};
 use nix::unistd::Pid;
 use serde::Deserialize;
@@ -1401,7 +1404,13 @@ fn main() -> Result<(), LauncherError> {
         let mut path = std::path::Path::new(&args.model_id).to_path_buf();
         let filename = if !path.exists() {
             // Assume it's a hub id
-            let api = Api::new()?;
+
+            let api = if let Ok(token) = std::env::var("HF_TOKEN") {
+                // env variable has precedence over on file token.
+                ApiBuilder::new().with_token(Some(token)).build()?
+            } else {
+                Api::new()?
+            };
             let repo = if let Some(ref revision) = args.revision {
                 api.repo(Repo::with_revision(
                     model_id,