[Model] Support DeepSeek-V4

examples/offline_inference/offline_inference.py

@@ -0,0 +1,48 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-MLU project
+
+import sys
+from vllm import LLM, SamplingParams
+
+
+def main(model_path):
+    # Sample prompts.
+    prompts = [
+        "The benefits of exercise include",
+        "The importance of reading books is",
+        "Gardening can be relaxing because",
+        "A good night's sleep is essential for",
+    ]
+    sampling_params = SamplingParams(
+        temperature=0.6, top_p=0.95, max_tokens=10)
+
+    # Create an LLM.
+    engine_args_dict = {
+        "model": model_path,
+        "tensor_parallel_size": 8,
+        "enable_expert_parallel": True,
+        "enable_prefix_caching": False,
+        "enforce_eager": True,
+        "trust_remote_code": True,
+        "max_num_seqs": len(prompts),
+        "max_model_len": 4096,
+        "block_size": 1,
+        "gpu_memory_utilization": 0.96,
+    }
+    llm = LLM(**engine_args_dict)
+
+    # Generate texts from the prompts.
+    outputs = llm.generate(prompts, sampling_params)
+
+    # Print the outputs.
+    for output in outputs:
+        prompt = output.prompt
+        generated_text = output.outputs[0].text
+        print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
+
+
+if __name__ == '__main__':
+    if len(sys.argv) < 2:
+        print("Usage: python offline_inference.py <model_path>")
+        sys.exit(1)
+    main(sys.argv[1])