[Bug]: Mistral-Small-24B-Instruct-2501 on V1 fails to start with Mistral tokenizer since V1 enabled guided decoding #14465
Description
Your current environment
The output of `python collect_env.py`
INFO 03-07 16:45:32 [__init__.py:256] Automatically detected platform cuda.
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: Arch Linux (x86_64)
GCC version: (GCC) 14.2.1 20250207
Clang version: 19.1.7
CMake version: version 3.30.0
Libc version: glibc-2.41
Python version: 3.12.9 (main, Feb 9 2025, 04:01:11) [GCC 14.2.1 20250128] (64-bit runtime)
Python platform: Linux-6.12.9-arch1-1-kvm-local-x86_64-with-glibc2.41
Is CUDA available: True
CUDA runtime version: 12.8.61
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090 Ti
Nvidia driver version: 570.124.04
cuDNN version: Probably one of the following:
/usr/lib/libcudnn.so.9.7.0
/usr/lib/libcudnn_adv.so.9.7.0
/usr/lib/libcudnn_cnn.so.9.7.0
/usr/lib/libcudnn_engines_precompiled.so.9.7.0
/usr/lib/libcudnn_engines_runtime_compiled.so.9.7.0
/usr/lib/libcudnn_graph.so.9.7.0
/usr/lib/libcudnn_heuristic.so.9.7.0
/usr/lib/libcudnn_ops.so.9.7.0
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: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 24
On-line CPU(s) list: 0-23
Vendor ID: GenuineIntel
Model name: 12th Gen Intel(R) Core(TM) i9-12900K
CPU family: 6
Model: 151
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 1
Stepping: 2
CPU(s) scaling MHz: 46%
CPU max MHz: 5200.0000
CPU min MHz: 800.0000
BogoMIPS: 6374.40
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 640 KiB (16 instances)
L1i cache: 768 KiB (16 instances)
L2 cache: 14 MiB (10 instances)
L3 cache: 30 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-23
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Reg file data sampling: Vulnerable
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Vulnerable
Vulnerability Spectre v1: Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2: Vulnerable; IBPB: disabled; STIBP: disabled; PBRSB-eIBRS: Vulnerable; BHI: Vulnerable
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] curated-transformers==0.1.1
[pip3] flashinfer==0.2.0.post1+cu124torch2.4
[pip3] flashinfer-python==0.2.0.post2+cu124torch2.5
[pip3] mypy==1.11.1
[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-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-cusparselt-cu12==0.6.2
[pip3] nvidia-ml-py==12.570.86
[pip3] nvidia-modelopt==0.21.0
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pynvml==12.0.0
[pip3] pyzmq==26.2.1
[pip3] sentence-transformers==3.2.0
[pip3] spacy-curated-transformers==0.3.0
[pip3] torch==2.5.1
[pip3] torchac_cuda==0.2.5
[pip3] torchaudio==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.49.0
[pip3] transformers-stream-generator==0.0.5
[pip3] triton==3.1.0
[conda] No relevant packages
ROCM Version: 6.3.42134-0
Neuron SDK Version: N/A
vLLM Version: 0.7.4.dev306+gb4c01560d.d20250307
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
�[4mGPU0 CPU Affinity NUMA Affinity GPU NUMA ID�[0m
GPU0 X 0-23 0 N/A
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
NCCL_SOCKET_IFNAME=br0
MAX_JOBS=16
CUDA_SDK_ROOT_DIR=/opt/cuda/targets/x86_64-linux
CUDA_SDK=/opt/cuda/targets/x86_64-linux
CUDA_PATH=/opt/cuda
CUDA_HOME=/opt/cuda
CUDA_HOME=/opt/cuda
LD_LIBRARY_PATH=/home/jeff/envs/python/virtualenvs/vllm312/lib/python3.12/site-packages/cv2/../../lib64:
NCCL_CUMEM_ENABLE=0
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY
🐛 Describe the bug
Cannot start Mistral-Small-24B-Instruct-2501 with the Mistral tokenizer on V1 anymore.
Traceback:
ERROR 03-07 16:37:49 [core.py:324] EngineCore hit an exception: Traceback (most recent call last):
ERROR 03-07 16:37:49 [core.py:324] File "/home/jeff/.virtualenvs/vllm312/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 316, in run_engine_core
ERROR 03-07 16:37:49 [core.py:324] engine_core = EngineCoreProc(*args, **kwargs)
ERROR 03-07 16:37:49 [core.py:324] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-07 16:37:49 [core.py:324] File "/home/jeff/.virtualenvs/vllm312/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 271, in __init__
ERROR 03-07 16:37:49 [core.py:324] super().__init__(vllm_config, executor_class, log_stats)
ERROR 03-07 16:37:49 [core.py:324] File "/home/jeff/.virtualenvs/vllm312/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 65, in __init__
ERROR 03-07 16:37:49 [core.py:324] self.structured_output_manager = StructuredOutputManager(vllm_config)
ERROR 03-07 16:37:49 [core.py:324] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-07 16:37:49 [core.py:324] File "/home/jeff/.virtualenvs/vllm312/lib/python3.12/site-packages/vllm/v1/structured_output/__init__.py", line 42, in __init__
ERROR 03-07 16:37:49 [core.py:324] tokenizer_info = xgr.TokenizerInfo.from_huggingface(
ERROR 03-07 16:37:49 [core.py:324] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-07 16:37:49 [core.py:324] File "/home/jeff/.virtualenvs/vllm312/lib/python3.12/site-packages/xgrammar/tokenizer_info.py", line 219, in from_huggingface
ERROR 03-07 16:37:49 [core.py:324] elif TokenizerInfo._is_tiktoken_tokenizer(tokenizer):
ERROR 03-07 16:37:49 [core.py:324] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-07 16:37:49 [core.py:324] File "/home/jeff/.virtualenvs/vllm312/lib/python3.12/site-packages/xgrammar/tokenizer_info.py", line 107, in _is_tiktoken_tokenizer
ERROR 03-07 16:37:49 [core.py:324] "vocab_file" in tokenizer.vocab_files_names
ERROR 03-07 16:37:49 [core.py:324] ^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-07 16:37:49 [core.py:324] AttributeError: 'MistralTokenizer' object has no attribute 'vocab_files_names'
ERROR 03-07 16:37:49 [core.py:324]
Before submitting a new issue...
- Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.