[Bug]: ValueError: This model does not support the 'reward' task. Supported tasks: {'embedding'}

[wccccp]

Your current environment

The output of `python collect_env.py`

Your output of `python collect_env.py` here

WARNING 12-16 10:58:46 cuda.py:23] You are using a deprecated `pynvml` package. Please install `nvidia-ml-py` instead, and make sure to uninstall `pynvml`. When both of them are installed, `pynvml` will take precedence and cause errors. See https://pypi.org/project/pynvml for more information. Warning: Your installation of OpenCV appears to be broken: module 'cv2.dnn' has no attribute 'DictValue'.Please follow the instructions at https://github.com/opencv/opencv-python/issues/884 to correct your environment. The import of cv2 has been skipped. Collecting environment information... PyTorch version: 2.5.1+cu124 Is debug build: False CUDA used to build PyTorch: 12.4 ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.30.2
Libc version: glibc-2.35

Python version: 3.10.12 (main, Jul 29 2024, 16:56:48) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-3.10.0-1160.99.1.el7.x86_64-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.6.20
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA A800-SXM4-80GB
GPU 1: NVIDIA A800-SXM4-80GB
GPU 2: NVIDIA A800-SXM4-80GB
GPU 3: NVIDIA A800-SXM4-80GB
GPU 4: NVIDIA A800-SXM4-80GB
GPU 5: NVIDIA A800-SXM4-80GB
GPU 6: NVIDIA A800-SXM4-80GB
GPU 7: NVIDIA A800-SXM4-80GB

Nvidia driver version: 535.104.05
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.3.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.3.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 48 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 64
On-line CPU(s) list: 0-63
Vendor ID: AuthenticAMD
Model name: AMD EPYC 7543 32-Core Processor
CPU family: 25
Model: 1
Thread(s) per core: 1
Core(s) per socket: 32
Socket(s): 2
Stepping: 1
Frequency boost: enabled
CPU max MHz: 2800.0000
CPU min MHz: 1500.0000
BogoMIPS: 5589.57
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc art rep_good nopl nonstop_tsc extd_apicid aperfmperf eagerfpu pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_l2 cpb cat_l3 cdp_l3 invpcid_single hw_pstate sme ssbd rsb_ctxsw ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif umip pku ospke vaes vpclmulqdq overflow_recov succor smca
Virtualization: AMD-V
L1d cache: 2 MiB (64 instances)
L1i cache: 2 MiB (64 instances)
L2 cache: 32 MiB (64 instances)
L3 cache: 512 MiB (16 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-31
NUMA node1 CPU(s): 32-63
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; Load fences, usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Full retpoline, IBPB
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cudnn-frontend==1.5.2
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-dali-cuda120==1.40.0
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-modelopt==0.15.0
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvimgcodec-cu12==0.3.0.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] nvidia-pyindex==1.0.9
[pip3] onnx==1.16.0
[pip3] optree==0.12.1
[pip3] pynvml==11.4.1
[pip3] pytorch-triton==3.0.0+dedb7bdf3
[pip3] pyzmq==26.1.0
[pip3] torch==2.5.1
[pip3] torch_tensorrt==2.5.0a0
[pip3] torchvision==0.20.1
[pip3] transformers==4.45.2
[pip3] triton==3.1.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.4.post1
vLLM Build Flags:
CUDA Archs: 5.2 6.0 6.1 7.0 7.2 7.5 8.0 8.6 8.7 9.0+PTX; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 NIC2 NIC3 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV8 NV8 NV8 NV8 NV8 NV8 NV8 PXB NODE SYS SYS 0-31 0 N/A
GPU1 NV8 X NV8 NV8 NV8 NV8 NV8 NV8 PXB NODE SYS SYS 0-31 0 N/A
GPU2 NV8 NV8 X NV8 NV8 NV8 NV8 NV8 NODE PXB SYS SYS 0-31 0 N/A
GPU3 NV8 NV8 NV8 X NV8 NV8 NV8 NV8 NODE PXB SYS SYS 0-31 0 N/A
GPU4 NV8 NV8 NV8 NV8 X NV8 NV8 NV8 SYS SYS PXB NODE 32-63 1 N/A
GPU5 NV8 NV8 NV8 NV8 NV8 X NV8 NV8 SYS SYS PXB NODE 32-63 1 N/A
GPU6 NV8 NV8 NV8 NV8 NV8 NV8 X NV8 SYS SYS NODE PXB 32-63 1 N/A
GPU7 NV8 NV8 NV8 NV8 NV8 NV8 NV8 X SYS SYS NODE PXB 32-63 1 N/A
NIC0 PXB PXB NODE NODE SYS SYS SYS SYS X NODE SYS SYS
NIC1 NODE NODE PXB PXB SYS SYS SYS SYS NODE X SYS SYS
NIC2 SYS SYS SYS SYS PXB PXB NODE NODE SYS SYS X NODE
NIC3 SYS SYS SYS SYS NODE NODE PXB PXB SYS SYS NODE X

Legend:

X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks

NIC Legend:

NIC0: mlx5_0
NIC1: mlx5_1
NIC2: mlx5_2
NIC3: mlx5_3

NVIDIA_VISIBLE_DEVICES=
CUBLAS_VERSION=12.6.0.22
NVIDIA_REQUIRE_CUDA=cuda>=9.0
CUDA_CACHE_DISABLE=1
TORCH_CUDA_ARCH_LIST=5.2 6.0 6.1 7.0 7.2 7.5 8.0 8.6 8.7 9.0+PTX
NCCL_VERSION=2.22.3
NVIDIA_DRIVER_CAPABILITIES=all
NVIDIA_VCUDA_PATH=cf7189f5124450360b3a8fc0718cec3f
NVIDIA_PRODUCT_NAME=PyTorch
CUDA_VERSION=12.6.0.022
PYTORCH_VERSION=2.5.0a0+872d972
PYTORCH_BUILD_NUMBER=0
CUDNN_FRONTEND_VERSION=1.5.2
CUDNN_VERSION=9.3.0.75
NVIDIA_CONTAINER_UUID=86303bfb-002a-45c7-bb1d-44c762834f6a
PYTORCH_HOME=/opt/pytorch/pytorch
LD_LIBRARY_PATH=/usr/local/lib/python3.10/dist-packages/cv2/../../lib64:/usr/local/lib/python3.10/dist-packages/torch/lib:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
NVIDIA_BUILD_ID=107063150
OMP_NUM_THREADS=32
CUDA_DRIVER_VERSION=560.35.03
PYTORCH_BUILD_VERSION=2.5.0a0+872d972
CUDA_HOME=/usr/local/cuda
CUDA_HOME=/usr/local/cuda
CUDA_MODULE_LOADING=LAZY
NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=
NVIDIA_PYTORCH_VERSION=24.08
TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1

Model Input Dumps

No response

🐛 Describe the bug

llm = LLM(model=model_path, task="reward")
(output,) = llm.encode("Hello, my name is")

data = output.outputs.data
print(f"Data: {data!r}")

WARNING 12-16 10:53:48 cuda.py:23] You are using a deprecated pynvml package. Please install nvidia-ml-py instead, and make sure to uninstall pynvml. When both of them are installed, pynvml will take precedence and cause errors. See https://pypi.org/project/pynvml for more information.
Warning: Your installation of OpenCV appears to be broken: module 'cv2.dnn' has no attribute 'DictValue'.Please follow the instructions at opencv/opencv-python#884 to correct your environment. The import of cv2 has been skipped.
Traceback (most recent call last):
File "/gpfs02/unifiedcsi/gpfs/csi-dfs-ti-platform-fs/AI_center_main/wcp/data_analysis_prompt/qwen_rm.py", line 6, in
llm = LLM(model=model_path, task="reward")
File "/usr/local/lib/python3.10/dist-packages/vllm/utils.py", line 1028, in inner
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/llm.py", line 210, in init
self.llm_engine = self.engine_class.from_engine_args(
File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 582, in from_engine_args
engine_config = engine_args.create_engine_config()
File "/usr/local/lib/python3.10/dist-packages/vllm/engine/arg_utils.py", line 959, in create_engine_config
model_config = self.create_model_config()
File "/usr/local/lib/python3.10/dist-packages/vllm/engine/arg_utils.py", line 891, in create_model_config
return ModelConfig(
File "/usr/local/lib/python3.10/dist-packages/vllm/config.py", line 264, in init
supported_tasks, task = self._resolve_task(task, self.hf_config)
File "/usr/local/lib/python3.10/dist-packages/vllm/config.py", line 358, in _resolve_task
raise ValueError(msg)
ValueError: This model does not support the 'reward' task. Supported tasks: {'embedding'}

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[DarkLight1337]

You're using the "latest" version of the docs which means the latest code on GitHub. If you're just using the latest released version, please refer to the "stable" version of the docs.

For the latest released version, you should use --task embedding.