diff --git a/README.md b/README.md
index 632333d..d5000fb 100644
--- a/README.md
+++ b/README.md
@@ -9,40 +9,7 @@ See complete documentation [here](https://ai2-climate-emulator.readthedocs.io/en
 
 ## Quickstart
 
-### 1. Install
-
-Clone this repository. Then assuming [conda](https://docs.conda.io/en/latest/)
-is available, run
-```
-make create_environment
-```
-to create a conda environment called `fme` with dependencies and source
-code installed. Alternatively, a Docker image can be built with `make build_docker_image`.
-You may verify installation by running `pytest fme/`.
-
-### 2. Download data and checkpoint
-
-The checkpoint and a 1-year subsample of the validation data are available at
-[this Zenodo repository](https://zenodo.org/doi/10.5281/zenodo.10791086).
-Download these to your local filesystem.
-
-Alternatively, if interested in the complete dataset, this is available via a public
-[requester pays](https://cloud.google.com/storage/docs/requester-pays)
-Google Cloud Storage bucket. For example, the 10-year validation data (approx. 190GB)
-can be downloaded with:
-```
-gsutil -m -u YOUR_GCP_PROJECT cp -r gs://ai2cm-public-requester-pays/2023-11-29-ai2-climate-emulator-v1/data/repeating-climSST-1deg-netCDFs/validation .
-```
-It is possible to download a portion of the dataset only, but it is necessary to have
-enough data to span the desired prediction period. The checkpoint is also available on GCS at
-`gs://ai2cm-public-requester-pays/2023-11-29-ai2-climate-emulator-v1/checkpoints/ace_ckpt.tar`.
-
-### 3. Update configuration and run
-Update the paths in the [example config](fme/docs/inference-config.yaml). Then in the
-`fme` conda environment, run inference with:
-```
-python -m fme.ace.inference fme/docs/inference-config.yaml
-```
+A quickstart guide may be found [here](https://ai2-climate-emulator.readthedocs.io/en/latest/quickstart.html).
 
 ## Available datasets
 Two versions of the dataset described in [arxiv:2310.02074](https://arxiv.org/abs/2310.02074)