[NPU]Support model Trinity-mini for Npu, accuracy 90% (#18172)

Co-authored-by: sglang-npu-bot <sglangnpu@163.com>

test/registered/ascend/llm_models/test_ascend_trinity_mini.py

@@ -0,0 +1,47 @@
+import unittest
+
+from sglang.test.ascend.gsm8k_ascend_mixin import GSM8KAscendMixin
+from sglang.test.ascend.test_ascend_utils import TRINITY_MINI_WEIGHTS_PATH
+from sglang.test.ci.ci_register import register_npu_ci
+from sglang.test.test_utils import CustomTestCase
+
+register_npu_ci(
+    est_time=400,
+    suite="nightly-2-npu-a3",
+    nightly=True,
+)
+
+
+class TestTrinityMini(GSM8KAscendMixin, CustomTestCase):
+    """Testcase: Verify that the inference accuracy of the arcee-ai/Trinity-Mini model on the GSM8K dataset is no less than 0.85.
+
+    [Test Category] Model
+    [Test Target] arcee-ai/Trinity-Mini
+    """
+
+    model = TRINITY_MINI_WEIGHTS_PATH
+    accuracy = 0.85
+    other_args = [
+        "--trust-remote-code",
+        "--mem-fraction-static",
+        "0.8",
+        "--attention-backend",
+        "ascend",
+        "--tp-size",
+        "2",
+        "--disable-cuda-graph",
+        "--disable-radix-cache",
+        "--disable-overlap-schedule",
+        "--context-length",
+        "4096",
+        "--max-running-requests",
+        "128",
+        "--chunked-prefill-size",
+        "-1",
+        "--chat-template",
+        f"{model}/chat_template.jinja",
+    ]
+
+
+if __name__ == "__main__":
+    unittest.main()