[Misc] Add SPDX-FileCopyrightText (#19100)

Signed-off-by: simon-mo <simon.mo@hey.com>

examples/offline_inference/basic/chat.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from vllm import LLM, EngineArgs
 from vllm.utils import FlexibleArgumentParser

examples/offline_inference/basic/classify.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from argparse import Namespace
 

examples/offline_inference/basic/embed.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from argparse import Namespace
 

examples/offline_inference/basic/generate.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from vllm import LLM, EngineArgs
 from vllm.utils import FlexibleArgumentParser

examples/offline_inference/basic/score.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from argparse import Namespace
 

examples/offline_inference/batch_llm_inference.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This example shows how to use Ray Data for data parallel batch inference.
 

examples/offline_inference/chat_with_tools.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 # ruff: noqa
 import json

examples/offline_inference/context_extension.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from vllm import LLM, SamplingParams
 

examples/offline_inference/data_parallel.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 Usage:
 Single node:

examples/offline_inference/disaggregated-prefill-v1/decode_example.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from vllm import LLM, SamplingParams
 from vllm.config import KVTransferConfig

examples/offline_inference/disaggregated-prefill-v1/prefill_example.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from vllm import LLM, SamplingParams
 from vllm.config import KVTransferConfig

examples/offline_inference/disaggregated_prefill.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This file demonstrates the example usage of disaggregated prefilling
 We will launch 2 vllm instances (GPU 0 for prefill and GPU 1 for decode),

examples/offline_inference/eagle.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import argparse
 import json
 import os

examples/offline_inference/embed_jina_embeddings_v3.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from argparse import Namespace
 

examples/offline_inference/embed_matryoshka_fy.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from argparse import Namespace
 

examples/offline_inference/encoder_decoder.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 Demonstrate prompting of text-to-text
 encoder/decoder models, specifically BART

examples/offline_inference/encoder_decoder_multimodal.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This example shows how to use vLLM for running offline inference with
 the explicit/implicit prompt format on enc-dec LMMs for text generation.

examples/offline_inference/llm_engine_example.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This file demonstrates using the `LLMEngine`
 for processing prompts with various sampling parameters.

examples/offline_inference/load_sharded_state.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 Validates the loading of a model saved with the sharded_state format.
 This script demonstrates how to load a model that was previously saved

examples/offline_inference/lora_with_quantization_inference.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This example shows how to use LoRA with different quantization techniques
 for offline inference.