[Model] Support Qwen2ForSequenceClassification (#4609)

Co-authored-by: ximing.wxm <ximing.wxm@antgroup.com>

test/srt/models/test_embedding_models.py

@@ -13,18 +13,20 @@
 # ==============================================================================
 
 import multiprocessing as mp
+import random
 import unittest
 
 import torch
 from transformers import AutoConfig, AutoTokenizer
 
 from sglang.test.runners import DEFAULT_PROMPTS, HFRunner, SRTRunner
-from sglang.test.test_utils import get_similarities
+from sglang.test.test_utils import get_similarities, is_in_ci
 
 MODELS = [
     ("Alibaba-NLP/gte-Qwen2-1.5B-instruct", 1, 1e-5),
     ("intfloat/e5-mistral-7b-instruct", 1, 1e-5),
     ("marco/mcdse-2b-v1", 1, 1e-5),
+    ("jason9693/Qwen2.5-1.5B-apeach", 1, 1e-5),
 ]
 TORCH_DTYPES = [torch.float16]
 
@@ -91,7 +93,12 @@ class TestEmbeddingModels(unittest.TestCase):
                 ), "embeddings are not all close"
 
     def test_prefill_logits(self):
-        for model, tp_size, prefill_tolerance in MODELS:
+        models_to_test = MODELS
+
+        if is_in_ci():
+            models_to_test = [random.choice(MODELS)]
+
+        for model, tp_size, prefill_tolerance in models_to_test:
             for torch_dtype in TORCH_DTYPES:
                 self.assert_close_prefill_logits(
                     DEFAULT_PROMPTS, model, tp_size, torch_dtype, prefill_tolerance