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kermitt2 · Nov 18, 2023 · 295d3a1 · 295d3a1
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 <h1>Run GROBID</h1>>
 
-The standard way to run Grobid is to use Docker for starting a Grobid server. 
+The standard way to run Grobid is to use [Docker](https://docs.docker.com/engine/understanding-docker/) for starting a Grobid server. 
 
-For installing Docker on your system, see [here](https://docs.docker.com/engine/understanding-docker/).
+For installing Docker on your system, please visit the official Docker documentation [here](https://docs.docker.com/get-docker/).
 
 For convenience, we provide two docker images:
 
-- the **full** image provides the best accuracy, because it includes all the required python and TensorFlow libraries, GPU support and all Deep Learning model resources. However it requires more resources, ideally a GPU (it will be automatically detected). If you have a limited amount of PDF, a good machine, and prioritize accuracy, use this Grobid flavor. To run this version of Grobid, the command is: 
+- the **full** image provides the best accuracy, because it includes all the required python and TensorFlow libraries, GPU support and all Deep Learning model resources. However it requires more resources, ideally a GPU (it will be automatically detected on Linux). If you have a limited amount of PDF, a good machine, and prioritize accuracy, use this Grobid flavor. To run this version of Grobid, the command is: 
 
 ```console
-docker run --rm --init --ulimit core=0 -p 8070:8070 lfoppiano/grobid:0.7.3
+docker run --rm --gpus all --init --ulimit core=0 -p 8070:8070 grobid/grobid:0.7.3
 ```
 
-- the **lightweight** one offers best performance in term of runtime, memory usage and Docker image size. However, it does not use some of the best performing models in term of accuracy. If you have a lot of PDF to process, a low resource system, and accuracy is not so important, use this flavor:
+- the **lightweight** image offers best runtime performance, memory usage and Docker image size. However, it does not use some of the best performing models in term of accuracy. If you have a lot of PDF to process, a low resource system, and accuracy is not so important, use this flavor:
 
 ```console
-docker run --rm --gpus all --init --ulimit core=0 -p 8070:8070 grobid/grobid:0.7.3
+docker run --rm --init --ulimit core=0 -p 8070:8070 lfoppiano/grobid:0.7.3
 ```
 
 More documentation on the Docker images can be found [here](Grobid-docker.md).