diff --git a/README.md b/README.md
index 3c659bbde5..d105a7aeb8 100644
--- a/README.md
+++ b/README.md
@@ -379,6 +379,28 @@ results = mteb.load_results(models=models, tasks=tasks)
 df = results_to_dataframe(results)
 ```
 
+</details>
+
+
+<details>
+  <summary>  Annotate Contamination in the training data of a model  </summary>
+
+### Annotate Contamination
+
+have your found contamination in the training data of a model? Please let us know, either by opening an issue or ideally by submitting a PR
+annotatig the training datasets of the model:
+
+```py
+model_w_contamination = ModelMeta(
+    name = "model-with-contamination"
+    ...
+    training_datasets: {"ArguAna": # name of dataset within MTEB
+                        ["test"]} # the splits that have been trained on
+    ...
+)
+```
+
+
 </details>
 
 <details>
diff --git a/mteb/model_meta.py b/mteb/model_meta.py
index 83653ec3d1..9ac590b5d6 100644
--- a/mteb/model_meta.py
+++ b/mteb/model_meta.py
@@ -72,8 +72,9 @@ class ModelMeta(BaseModel):
             in the Latin script.
         use_instructions: Whether the model uses instructions E.g. for prompt-based models. This also include models that require a specific format for
             input such as "query: {document}" or "passage: {document}".
-        zero_shot_benchmarks: A list of benchmarks on which the model has been evaluated in a zero-shot setting. By default we assume that all models
-            are evaluated non-zero-shot unless specified otherwise.
+        training_datasets: A dictionary of datasets that the model was trained on. Names should be names as their appear in `mteb` for example
+            {"ArguAna": ["test"]} if the model is trained on the ArguAna test set. This field is used to determine if a model generalizes zero-shot to
+            a benchmark as well as mark dataset contaminations.
         adapted_from: Name of the model from which this model is adapted from. For quantizations, fine-tunes, long doc extensions, etc.
         superseded_by: Name of the model that supersedes this model, e.g. nvidia/NV-Embed-v2 supersedes v1.
     """
@@ -97,7 +98,7 @@ class ModelMeta(BaseModel):
     reference: STR_URL | None = None
     similarity_fn_name: DISTANCE_METRICS | None = None
     use_instructions: bool | None = None
-    zero_shot_benchmarks: list[str] | None = None
+    training_datasets: dict[str, list[str]] | None = None
     adapted_from: str | None = None
     superseded_by: str | None = None