[Misc] Add SPDX-FileCopyrightText (#19100)

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

examples/offline_inference/metrics.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from vllm import LLM, SamplingParams
 from vllm.v1.metrics.reader import Counter, Gauge, Histogram, Vector

examples/offline_inference/mistral-small.py

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

examples/offline_inference/mlpspeculator.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This file demonstrates the usage of text generation with an LLM model,
 comparing the performance with and without speculative decoding.

examples/offline_inference/multilora_inference.py

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

examples/offline_inference/neuron.py

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

examples/offline_inference/neuron_eagle.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This example shows how to run offline inference with an EAGLE speculative
 decoding model on neuron. To use EAGLE speculative decoding, you must use

examples/offline_inference/neuron_int8_quantization.py

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

examples/offline_inference/neuron_multimodal.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import requests
 import torch
 from neuronx_distributed_inference.models.mllama.utils import add_instruct

examples/offline_inference/neuron_speculation.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This example shows how to run offline inference with a speculative
 decoding model on neuron.

examples/offline_inference/prefix_caching.py

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

examples/offline_inference/prithvi_geospatial_mae.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 This is a demo script showing how to use the
 PrithviGeospatialMAE model with vLLM

examples/offline_inference/profiling.py

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

examples/offline_inference/profiling_tpu/profiling.py

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

examples/offline_inference/prompt_embed_inference.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 Demonstrates how to generate prompt embeddings using
 Hugging Face Transformers  and use them as input to vLLM

examples/offline_inference/qwen2_5_omni/only_thinker.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 correct prompt format on Qwen2.5-Omni (thinker only).

examples/offline_inference/qwen_1m.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import os
 from urllib.request import urlopen
 

examples/offline_inference/reproducibility.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 Demonstrates how to achieve reproducibility in vLLM.
 

examples/offline_inference/rlhf.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 a simple demonstration of RLHF with vLLM, inspired by
 the OpenRLHF framework https://github.com/OpenRLHF/OpenRLHF .

examples/offline_inference/rlhf_colocate.py

 # SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """
 a simple demonstration to show how to co-locate
 vLLM worker with training actors on the same GPUs,

examples/offline_inference/rlhf_utils.py

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