add IAM4VP model

README.md

@@ -9,12 +9,12 @@ library_name: pytorch
 
 ## Model Description
 
-These models are trained to predict future frames of satellite data from past frames. The model uses 3 hours
-of recent satellite imagery at 15 minute intervals and predicts 3 hours into the future also at
-15 minute intervals. The satellite inputs and predictions are multispectral with 11 channels.
+These models are trained to predict future frames of satellite data from past frames. The model uses
+3 hours of recent satellite imagery at 15 minute intervals and predicts 3 hours into the future also
+at 15 minute intervals. The satellite inputs and predictions are multispectral with 11 channels.
 
 
-See [1] for the repo used to train the model.
+See [1] and [2] for the repo used to train these model.
 
 - **Developed by:** Open Climate Fix and the Alan Turing Institute
 - **License:** mit
@@ -27,7 +27,7 @@ See [1] for the repo used to train the model.
 This was trained on EUMETSAT satellite imagery derived from the data stored in [this google public 
 dataset](https://console.cloud.google.com/marketplace/product/bigquery-public-data/eumetsat-seviri-rss?hl=en-GB&inv=1&invt=AbniZA&project=solar-pv-nowcasting&pli=1). 
 
-The data was processed using the protocol in [2]
+The data was processed using the protocol in [3]
 
 
 ## Results
@@ -37,7 +37,10 @@ See the READMEs in each model dir for links to the wandb training runs
 
 ## Usage
 
-These models rely on [1] being installed. Example usage to load the model is shown below
+The models in this repo have slightly different requirements. The SimVP and eartherformer models 
+require [1] to be installed and the IAM4VP model requires [2].
+
+The SimVP and earthfomer models can be loaded like:
 
 ```{python}
 import hydra
@@ -47,8 +50,8 @@ from safetensors.torch import load_model
 
 
 REPO_ID = "openclimatefix/cloudcasting_example_models"
-REVISION = <commit-id>
-MODEL = "simvp_model"
+REVISION = None # None for latest or set <commit-id>
+MODEL = "simvp_model" # simvp_model or earthformer_model
 
 # Download the model checkpoints
 hf_download_dir = snapshot_download(
@@ -57,18 +60,47 @@ hf_download_dir = snapshot_download(
 )
 
 # Create the model object
-with open(f"{hf_download_dir}/model_config.yaml", "r", encoding="utf-8") as f:
+with open(f"{hf_download_dir}/{MODEL}/model_config.yaml", "r", encoding="utf-8") as f:
     model = hydra.utils.instantiate(yaml.safe_load(f))
 
 # Load the model weights
 load_model(
     model,
-    filename=f"{hf_download_dir}/model.safetensors", 
+    filename=f"{hf_download_dir}/{MODEL}/model.safetensors", 
     strict=True,
 )
 ```
 
-### Software
+The IAM4VP model can be loaded like
+
+```
+from huggingface_hub import snapshot_download
+from ocf_iam4vp import IAM4VPLightning
+
+
+REPO_ID = "openclimatefix/cloudcasting_example_models"
+REVISION = None # None for latest or set <commit-id>
+
+# Download the model checkpoints
+hf_download_dir = snapshot_download(
+    repo_id=REPO_ID,
+    revision=REVISION,
+)
+
+
+model = IAM4VPLightning.load_from_checkpoint(
+    f"{hf_download_dir}/iam4vp/iam4vp_checkpoint_0.4.3.ckpt", 
+    num_forecast_steps=12,
+).model
+```
+
+
+See the cloudcasting package [3]
+
+
+### Packages
 
 - [1] https://github.com/openclimatefix/sat_pred
-- [2] https://github.com/alan-turing-institute/cloudcasting
+- [2] https://github.com/alan-turing-institute/ocf-iam4vp
+- [3] https://github.com/alan-turing-institute/cloudcasting
+

iam4vp/README.md

@@ -0,0 +1,38 @@
+---
+language: en
+license: mit
+library_name: pytorch
+---
+
+
+# Cloudcasting
+
+## Model Description
+
+<!-- Provide a longer summary of what this model is/does. -->
+This model is trained to predict future frames of satellite data from past frames. It takes 3 hours
+of recent satellkite imagery at 15 minute intervals and predicts 3 hours into the future also at
+15 minute intervals. The satellite inputs and predictions are multispectral with 11 channels.
+
+
+See [1] for the repo used to train the model.
+
+- **Developed by:** Open Climate Fix and the Alan Turing Institute
+- **License:** mit
+
+
+# Training Details
+
+## Data
+
+<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+This was trained on EUMETSAT satellite imagery derived from the data stored in [this google public 
+dataset](https://console.cloud.google.com/marketplace/product/bigquery-public-data/eumetsat-seviri-rss?hl=en-GB&inv=1&invt=AbniZA&project=solar-pv-nowcasting&pli=1). 
+
+The data was processed using the protocol in [2]
+
+
+### Software
+
+- [1] https://github.com/alan-turing-institute/ocf-iam4vp
+- [2] https://github.com/alan-turing-institute/cloudcasting

iam4vp/iam4vp_checkpoint_0.4.3.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:511d803cf6907bb041de85ffdf02b44a2ab201bb3c7254fc5966d9820557dd9b
+size 24569644