Merge similar examples in offline_inference into single basic example (#12737)

examples/offline_inference/basic/classify.py

@@ -0,0 +1,42 @@
+# SPDX-License-Identifier: Apache-2.0
+
+from argparse import Namespace
+
+from vllm import LLM, EngineArgs
+from vllm.utils import FlexibleArgumentParser
+
+
+def main(args: Namespace):
+    # Sample prompts.
+    prompts = [
+        "Hello, my name is",
+        "The president of the United States is",
+        "The capital of France is",
+        "The future of AI is",
+    ]
+
+    # Create an LLM.
+    # You should pass task="classify" for classification models
+    model = LLM(**vars(args))
+
+    # Generate logits. The output is a list of ClassificationRequestOutputs.
+    outputs = model.classify(prompts)
+
+    # Print the outputs.
+    for prompt, output in zip(prompts, outputs):
+        probs = output.outputs.probs
+        probs_trimmed = ((str(probs[:16])[:-1] +
+                          ", ...]") if len(probs) > 16 else probs)
+        print(f"Prompt: {prompt!r} | "
+              f"Class Probabilities: {probs_trimmed} (size={len(probs)})")
+
+
+if __name__ == "__main__":
+    parser = FlexibleArgumentParser()
+    parser = EngineArgs.add_cli_args(parser)
+    # Set example specific arguments
+    parser.set_defaults(model="jason9693/Qwen2.5-1.5B-apeach",
+                        task="classify",
+                        enforce_eager=True)
+    args = parser.parse_args()
+    main(args)