@@ -83,6 +83,7 @@ volume=$PWD/data # share a volume with the Docker container to avoid downloading
...
@@ -83,6 +83,7 @@ volume=$PWD/data # share a volume with the Docker container to avoid downloading
docker run --gpus all --shm-size 1g -p 8080:80 -v$volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id$model--num-shard$num_shard
docker run --gpus all --shm-size 1g -p 8080:80 -v$volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id$model--num-shard$num_shard
```
```
**Note:** To use 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 11.8 or higher.
You can then query the model using either the `/generate` or `/generate_stream` routes:
You can then query the model using either the `/generate` or `/generate_stream` routes:
...
@@ -119,8 +120,6 @@ for response in client.generate_stream("What is Deep Learning?", max_new_tokens=
...
@@ -119,8 +120,6 @@ for response in client.generate_stream("What is Deep Learning?", max_new_tokens=
print(text)
print(text)
```
```
**Note:** To use GPUs, you need to install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html).
### API documentation
### API documentation
You can consult the OpenAPI documentation of the `text-generation-inference` REST API using the `/docs` route.
You can consult the OpenAPI documentation of the `text-generation-inference` REST API using the `/docs` route.