diff --git a/assets/ar/sentiment_emotion_others/sentiment/ArSAS_JAIS13b_ZeroShot.py b/assets/ar/sentiment_emotion_others/sentiment/ArSAS_JAIS13b_ZeroShot.py
new file mode 100644
index 00000000..a8fa4ea2
--- /dev/null
+++ b/assets/ar/sentiment_emotion_others/sentiment/ArSAS_JAIS13b_ZeroShot.py
@@ -0,0 +1,52 @@
+from llmebench.datasets import ArSASDataset
+from llmebench.models import FastChatModel
+from llmebench.tasks import SentimentTask
+
+
+def metadata():
+    return {
+        "author": "Arabic Language Technologies, QCRI, HBKU",
+        "model": "Jais-13b-chat",
+        "description": "Locally hosted Jais-13b-chat model using FastChat.",
+    }
+
+
+def config():
+    return {
+        "dataset": ArSASDataset,
+        "task": SentimentTask,
+        "model": FastChatModel,
+    }
+
+
+def prompt(input_sample):
+    base_prompt = (
+        f'Classify the sentiment of the following sentence as "Positive", "Negative", "Neutral" or "Mixed". Output only the label and nothing else.\n'
+        f"Sentence: {input_sample}\n"
+        f"Label: "
+    )
+
+    return [
+        {
+            "role": "user",
+            "content": base_prompt,
+        },
+    ]
+
+
+def post_process(response):
+    out = response["choices"][0]["message"]["content"]
+    out = out.strip().lower()
+
+    if "i apologize" in out:
+        return None
+
+    j = out.find("label:")
+    if j > 0:
+        out = out[j + len("label:") :]
+    else:
+        j = out.find(" is:\n\n")
+        if j > 0:
+            out = out[j + len(" is:\n\n") :]
+    out = out.strip().title()
+    return out