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vllm - 💡(How to fix) Fix [Bug]: TypeError: transformers.tokenization_utils_tokenizers.TokenizersBackend._patch_mistral_regex() got multiple values for keyword argument 'fix_mistral_regex' [3 comments, 2 participants]

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vllm-project/vllm#37967•Fetched 2026-04-08 01:22:24
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tech112233445566tech112233445566
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tech112233445566tech112233445566yanghui1-archyanghui1-arch
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commented ×3added_to_project_v2 ×1labeled ×1project_v2_item_status_changed ×1

Fix Action

Fix / Workaround

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 208 On-line CPU(s) list: 0-207 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Platinum 8470Q CPU family: 6 Model: 143 Thread(s) per core: 2 Core(s) per socket: 52 Socket(s): 2 Stepping: 8 Frequency boost: enabled CPU max MHz: 2101.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 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 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 4.9 MiB (104 instances) L1i cache: 3.3 MiB (104 instances) L2 cache: 208 MiB (104 instances) L3 cache: 210 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-51,104-155 NUMA node1 CPU(s): 52-103,156-207 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; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

TypeError: transformers.tokenization_utils_tokenizers.TokenizersBackend._patch_mistral_regex() got multiple values for keyword argument 'fix_mistral_regex'

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Your current environment

Collecting environment information...

    System Info

============================== 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 3.22.1 Libc version : glibc-2.35

============================== PyTorch Info

PyTorch version : 2.10.0+cu128 Is debug build : False CUDA used to build PyTorch : 12.8 ROCM used to build PyTorch : N/A

============================== Python Environment

Python version : 3.12.3 | packaged by Anaconda, Inc. | (main, May 6 2024, 19:46:43) [GCC 11.2.0] (64-bit runtime) Python platform : Linux-5.15.0-78-generic-x86_64-with-glibc2.35

============================== CUDA / GPU Info

Is CUDA available : True CUDA runtime version : 12.4.131 CUDA_MODULE_LOADING set to : GPU models and configuration : GPU 0: NVIDIA GeForce RTX 5090 Nvidia driver version : 580.105.08 cuDNN version : Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.1.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.1.0 HIP runtime version : N/A MIOpen runtime version : N/A Is XNNPACK available : True

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 208 On-line CPU(s) list: 0-207 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Platinum 8470Q CPU family: 6 Model: 143 Thread(s) per core: 2 Core(s) per socket: 52 Socket(s): 2 Stepping: 8 Frequency boost: enabled CPU max MHz: 2101.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 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 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 4.9 MiB (104 instances) L1i cache: 3.3 MiB (104 instances) L2 cache: 208 MiB (104 instances) L3 cache: 210 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-51,104-155 NUMA node1 CPU(s): 52-103,156-207 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; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

============================== Versions of relevant libraries

[pip3] flashinfer-python==0.6.6 [pip3] numpy==2.1.3 [pip3] nvidia-cublas-cu12==12.8.4.1 [pip3] nvidia-cuda-cupti-cu12==12.8.90 [pip3] nvidia-cuda-nvrtc-cu12==12.8.93 [pip3] nvidia-cuda-runtime-cu12==12.8.90 [pip3] nvidia-cudnn-cu12==9.10.2.21 [pip3] nvidia-cudnn-frontend==1.18.0 [pip3] nvidia-cufft-cu12==11.3.3.83 [pip3] nvidia-cufile-cu12==1.13.1.3 [pip3] nvidia-curand-cu12==10.3.9.90 [pip3] nvidia-cusolver-cu12==11.7.3.90 [pip3] nvidia-cusparse-cu12==12.5.8.93 [pip3] nvidia-cusparselt-cu12==0.7.1 [pip3] nvidia-cutlass-dsl==4.4.2 [pip3] nvidia-cutlass-dsl-libs-base==4.4.2 [pip3] nvidia-ml-py==13.595.45 [pip3] nvidia-nccl-cu12==2.27.5 [pip3] nvidia-nvjitlink-cu12==12.8.93 [pip3] nvidia-nvshmem-cu12==3.4.5 [pip3] nvidia-nvtx-cu12==12.8.90 [pip3] pyzmq==26.2.0 [pip3] torch==2.10.0 [pip3] torch_c_dlpack_ext==0.1.5 [pip3] torchaudio==2.10.0 [pip3] torchvision==0.25.0 [pip3] transformers==5.0.0rc0 [pip3] triton==3.6.0 [conda] flashinfer-python 0.6.6 pypi_0 pypi [conda] numpy 2.1.3 pypi_0 pypi [conda] nvidia-cublas-cu12 12.8.4.1 pypi_0 pypi [conda] nvidia-cuda-cupti-cu12 12.8.90 pypi_0 pypi [conda] nvidia-cuda-nvrtc-cu12 12.8.93 pypi_0 pypi [conda] nvidia-cuda-runtime-cu12 12.8.90 pypi_0 pypi [conda] nvidia-cudnn-cu12 9.10.2.21 pypi_0 pypi [conda] nvidia-cudnn-frontend 1.18.0 pypi_0 pypi [conda] nvidia-cufft-cu12 11.3.3.83 pypi_0 pypi [conda] nvidia-cufile-cu12 1.13.1.3 pypi_0 pypi [conda] nvidia-curand-cu12 10.3.9.90 pypi_0 pypi [conda] nvidia-cusolver-cu12 11.7.3.90 pypi_0 pypi [conda] nvidia-cusparse-cu12 12.5.8.93 pypi_0 pypi [conda] nvidia-cusparselt-cu12 0.7.1 pypi_0 pypi [conda] nvidia-cutlass-dsl 4.4.2 pypi_0 pypi [conda] nvidia-cutlass-dsl-libs-base 4.4.2 pypi_0 pypi [conda] nvidia-ml-py 13.595.45 pypi_0 pypi [conda] nvidia-nccl-cu12 2.27.5 pypi_0 pypi [conda] nvidia-nvjitlink-cu12 12.8.93 pypi_0 pypi [conda] nvidia-nvshmem-cu12 3.4.5 pypi_0 pypi [conda] nvidia-nvtx-cu12 12.8.90 pypi_0 pypi [conda] pyzmq 26.2.0 pypi_0 pypi [conda] torch 2.10.0 pypi_0 pypi [conda] torch-c-dlpack-ext 0.1.5 pypi_0 pypi [conda] torchaudio 2.10.0 pypi_0 pypi [conda] torchvision 0.25.0 pypi_0 pypi [conda] transformers 5.0.0rc0 pypi_0 pypi [conda] triton 3.6.0 pypi_0 pypi

============================== vLLM Info

ROCM Version : Could not collect vLLM Version : 0.18.0 vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled GPU Topology: GPU0 NIC0 NIC1 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NODE NODE 0-51,104-155 0 N/A NIC0 NODE X PIX NIC1 NODE PIX 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

============================== Environment Variables

NVIDIA_VISIBLE_DEVICES=void NVIDIA_REQUIRE_CUDA=cuda>=12.4 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536 NCCL_VERSION=2.21.5-1 NVIDIA_DRIVER_CAPABILITIES=compute,utility,graphics,video NVIDIA_PRODUCT_NAME=CUDA CUDA_VERSION=12.4.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 OMP_NUM_THREADS=25 NVIDIA_CTK_LIBCUDA_DIR=/usr/lib/x86_64-linux-gnu MKL_NUM_THREADS=25 PYTORCH_NVML_BASED_CUDA_CHECK=1 TORCHINDUCTOR_COMPILE_THREADS=1 TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_root

🐛 Describe the bug

TypeError: transformers.tokenization_utils_tokenizers.TokenizersBackend._patch_mistral_regex() got multiple values for keyword argument 'fix_mistral_regex'

MODEL_USE:Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2 我有看到说用加这个参数可以去除这个bug，我加在tokenizer_config.json中，但是报错了

I have see the method of adding the key word can solve the problem,but my environment have some problems

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extent analysis

Fix Plan

The error message indicates that the _patch_mistral_regex function is receiving multiple values for the fix_mistral_regex keyword argument. To fix this issue, you need to update the transformers library to a version that does not have this bug.

Here are the steps to fix the issue:

  • Update the transformers library to the latest version using pip:
pip install --upgrade transformers
  • If you are using a requirements.txt file, update the transformers version in the file and then run:
pip install -r requirements.txt
  • Alternatively, you can try downgrading the transformers library to a version that does not have this bug. For example:
pip install transformers==4.24.0
  • After updating the transformers library, try running your code again to see if the issue is resolved.

Verification

To verify that the fix worked, try running your code again and check if the TypeError is still occurring. If the error is resolved, you should be able to run your code without any issues.

Extra Tips

  • Make sure to check the compatibility of the transformers library with your other dependencies, such as torch and torchvision.
  • If you are using a virtual environment, make sure to activate it before installing or updating packages.
  • If you are still experiencing issues after updating the transformers library, try checking the library's documentation or issues page for any known bugs or compatibility issues.

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