Add JAIS for ANSStance asset

assets/ar/sentiment_emotion_others/stance_detection/ANSStance_JAIS13b_ZeroShot.py

@@ -0,0 +1,61 @@
+from llmebench.datasets import ANSStanceDataset
+from llmebench.models import FastChatModel
+from llmebench.tasks import StanceTask
+
+
+def metadata():
+    return {
+        "author": "Arabic Language Technologies, QCRI, HBKU",
+        "model": "JAIS-13b",
+        "description": "Locally hosted JAIS-13b-chat model using FastChat.",
+        "scores": {"Macro-F1": ""},
+    }
+
+
+def config():
+    return {
+        "dataset": ANSStanceDataset,
+        "task": StanceTask,
+        "model": FastChatModel,
+        "model_args": {
+            "class_labels": ["agree", "disagree"],
+            "max_tries": 30,
+        },
+    }
+
+
+def prompt(input_sample):
+    ref_s = input_sample["sentence_1"]
+    claim = input_sample["sentence_2"]
+    base_prompt = (
+        f"Given a reference sentence and a claim, predict whether the claim agrees or disagrees with the reference sentence. Reply only using 'agree', 'disagree', or use 'other' if the sentence and claim are unrelated."
+        f"\n\n"
+        f"reference sentence: {ref_s}"
+        f"\nclaim: {claim}"
+        f"\nlabel: \n"
+    )
+
+    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.lower()