vllm - ✅(Solved) Fix [Bug]: Unsharded model cannot be loaded [1 pull requests, 1 participants]

vllm2026-04-02 17:01:13

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vllm-project/vllm#38829•Fetched 2026-04-08 02:34:39

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shubhamjain0594

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shubhamjain0594

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cross-referenced ×1labeled ×1referenced ×1

Error Message

When the model is stored without sharding, it is stored as model.safetensors and it seems vllm doesn't find it and instead gives an error no model found. When storing it sharded as model-00000-of-00001.safetensors it does seem to work. This becomes an issue when merging (with LoRA) and storing small models that don't need sharding like Qwen/Qwen3-0.6B. These are by default saved as model.safetensors.

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): 384 On-line CPU(s) list: 0-383 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) 6972P CPU family: 6 Model: 173 Thread(s) per core: 2 Core(s) per socket: 96 Socket(s): 2 Stepping: 1 CPU max MHz: 3900.0000 CPU min MHz: 800.0000 BogoMIPS: 4800.00 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 monitor 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 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow 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 user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi vnmi 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 ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities ibpb_exit_to_user Virtualization: VT-x L1d cache: 9 MiB (192 instances) L1i cache: 12 MiB (192 instances) L2 cache: 384 MiB (192 instances) L3 cache: 960 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-95,192-287 NUMA node1 CPU(s): 96-191,288-383 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: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

PR fix notes

PR #39035: [Bugfix] Fix unsharded model.safetensors not found during weight download

Repository: vllm-project/vllm
Author: Dharit13
State: closed | merged: False
Link: https://github.com/vllm-project/vllm/pull/39035

Description (problem / solution / changelog)

Summary

Fixes download_weights_from_hf() failing to find unsharded model.safetensors files
The root cause is fnmatch.filter(file_list, "*.safetensors") where file_list contains full repo-relative paths from HfFileSystem.ls() (e.g. org/model/model.safetensors). Since fnmatch's * does not match /, the pattern never matches, causing the code to fall through to *.bin and skip the safetensors file entirely.
Fix: match patterns against os.path.basename() of each path instead of the full path

Closes #38829

Why this is not duplicating an existing PR

Verified via:

gh pr list --repo vllm-project/vllm --state open --search "38829 in:body"
gh pr list --repo vllm-project/vllm --state open --search "unsharded model.safetensors"

Both returned zero results.

Test commands run and results

$ python -m pytest tests/model_executor/test_weight_utils.py::TestDownloadWeightsPatternSelection -v
======================== 3 passed, 16 warnings in 2.90s ========================

Three new regression tests added:

test_unsharded_safetensors_pattern_selected — verifies single model.safetensors with full repo paths is matched
test_sharded_safetensors_pattern_selected — verifies sharded files with index take the index path
test_only_bin_files_selects_bin — verifies .bin-only repos correctly select *.bin

AI Assistance Disclosure

This PR was developed with AI assistance (Claude). All code has been reviewed and tested by the human submitter.

Made with Cursor

Changed files

tests/model_executor/test_weight_utils.py (modified, +138/-0)
vllm/model_executor/model_loader/weight_utils.py (modified, +5/-1)

Code Example

Collecting environment information...
uv is set
==============================
        System Info
==============================
OS                           : Ubuntu 22.04.5 LTS (x86_64)
GCC version                  : (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0
Clang version                : Could not collect
CMake version                : Could not collect
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               : 3.10.12 (main, Mar  3 2026, 11:56:32) [GCC 11.4.0] (64-bit runtime)
Python platform              : Linux-6.8.0-90-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 RTX PRO 6000 Blackwell Server Edition
GPU 1: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 2: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 3: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 4: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 5: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 6: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 7: NVIDIA RTX PRO 6000 Blackwell Server Edition

Nvidia driver version        : 580.105.08
cuDNN version                : Could not collect
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):                               384
On-line CPU(s) list:                  0-383
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) 6972P
CPU family:                           6
Model:                                173
Thread(s) per core:                   2
Core(s) per socket:                   96
Socket(s):                            2
Stepping:                             1
CPU max MHz:                          3900.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4800.00
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 monitor 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 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow 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 user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi vnmi 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 ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities ibpb_exit_to_user
Virtualization:                       VT-x
L1d cache:                            9 MiB (192 instances)
L1i cache:                            12 MiB (192 instances)
L2 cache:                             384 MiB (192 instances)
L3 cache:                             960 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-95,192-287
NUMA node1 CPU(s):                    96-191,288-383
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: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Vulnerability Vmscape:                Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.4
[pip3] mypy-extensions==1.1.0
[pip3] numpy==2.2.6
[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==13.590.48
[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==27.1.0
[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==4.57.6
[pip3] triton==3.6.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.17.1
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
  	[4mGPU0	GPU1	GPU2	GPU3	GPU4	GPU5	GPU6	GPU7	CPU Affinity	NUMA Affinity	GPU NUMA ID[0m
GPU0	 X 	PIX	NODE	NODE	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU1	PIX	 X 	NODE	NODE	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU2	NODE	NODE	 X 	PIX	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU3	NODE	NODE	PIX	 X 	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU4	SYS	SYS	SYS	SYS	 X 	PIX	NODE	NODE	96-191,288-383	1		N/A
GPU5	SYS	SYS	SYS	SYS	PIX	 X 	NODE	NODE	96-191,288-383	1		N/A
GPU6	SYS	SYS	SYS	SYS	NODE	NODE	 X 	PIX	96-191,288-383	1		N/A
GPU7	SYS	SYS	SYS	SYS	NODE	NODE	PIX	 X 	96-191,288-383	1		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

==============================
     Environment Variables
==============================
CUDA_HOME=/usr/local/cuda
CUDA_HOME=/usr/local/cuda
LD_LIBRARY_PATH=:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_<user>

RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>

Collecting environment information...
uv is set
==============================
        System Info
==============================
OS                           : Ubuntu 22.04.5 LTS (x86_64)
GCC version                  : (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0
Clang version                : Could not collect
CMake version                : Could not collect
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               : 3.10.12 (main, Mar  3 2026, 11:56:32) [GCC 11.4.0] (64-bit runtime)
Python platform              : Linux-6.8.0-90-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 RTX PRO 6000 Blackwell Server Edition
GPU 1: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 2: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 3: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 4: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 5: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 6: NVIDIA RTX PRO 6000 Blackwell Server Edition
GPU 7: NVIDIA RTX PRO 6000 Blackwell Server Edition

Nvidia driver version        : 580.105.08
cuDNN version                : Could not collect
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):                               384
On-line CPU(s) list:                  0-383
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) 6972P
CPU family:                           6
Model:                                173
Thread(s) per core:                   2
Core(s) per socket:                   96
Socket(s):                            2
Stepping:                             1
CPU max MHz:                          3900.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4800.00
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 monitor 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 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow 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 user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi vnmi 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 ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities ibpb_exit_to_user
Virtualization:                       VT-x
L1d cache:                            9 MiB (192 instances)
L1i cache:                            12 MiB (192 instances)
L2 cache:                             384 MiB (192 instances)
L3 cache:                             960 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-95,192-287
NUMA node1 CPU(s):                    96-191,288-383
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: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Vulnerability Vmscape:                Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.4
[pip3] mypy-extensions==1.1.0
[pip3] numpy==2.2.6
[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==13.590.48
[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==27.1.0
[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==4.57.6
[pip3] triton==3.6.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.17.1
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
  	[4mGPU0	GPU1	GPU2	GPU3	GPU4	GPU5	GPU6	GPU7	CPU Affinity	NUMA Affinity	GPU NUMA ID[0m
GPU0	 X 	PIX	NODE	NODE	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU1	PIX	 X 	NODE	NODE	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU2	NODE	NODE	 X 	PIX	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU3	NODE	NODE	PIX	 X 	SYS	SYS	SYS	SYS	0-95,192-287	0		N/A
GPU4	SYS	SYS	SYS	SYS	 X 	PIX	NODE	NODE	96-191,288-383	1		N/A
GPU5	SYS	SYS	SYS	SYS	PIX	 X 	NODE	NODE	96-191,288-383	1		N/A
GPU6	SYS	SYS	SYS	SYS	NODE	NODE	 X 	PIX	96-191,288-383	1		N/A
GPU7	SYS	SYS	SYS	SYS	NODE	NODE	PIX	 X 	96-191,288-383	1		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

==============================
     Environment Variables
==============================
CUDA_HOME=/usr/local/cuda
CUDA_HOME=/usr/local/cuda
LD_LIBRARY_PATH=:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_<user>

</details>

🐛 Describe the bug

Before submitting a new issue...

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extent analysis

TL;DR

The issue can be resolved by storing the model in a sharded format, such as model-00000-of-00001.safetensors, to ensure vLLM can find it.

Guidance

Verify that the model is being stored in the correct location and that the file name matches the expected format.
Try storing the model with sharding enabled, even for small models, to see if this resolves the issue.
Check the vLLM documentation for any specific requirements or restrictions on model file names and storage formats.
Consider modifying the model saving code to always store models in the sharded format, to avoid this issue in the future.

Example

No code example is provided as the issue seems to be related to the model storage format rather than a specific code snippet.

Notes

The issue may be specific to the vLLM version being used (0.17.1), and it's possible that this is a known issue or a limitation of the current implementation.

Recommendation

Apply workaround: Store the model in a sharded format, such as model-00000-of-00001.safetensors, to ensure vLLM can find it. This is a simple and effective solution to the problem, and it does not require any significant changes to the code or infrastructure.

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vllm - ✅(Solved) Fix [Bug]: Unsharded model cannot be loaded [1 pull requests, 1 participants]

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PR #39035: [Bugfix] Fix unsharded model.safetensors not found during weight download

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vllm - ✅(Solved) Fix [Bug]: Unsharded model cannot be loaded [1 pull requests, 1 participants]

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Error Message

Fix Action

Fix / Workaround

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

PR fix notes

PR #39035: [Bugfix] Fix unsharded model.safetensors not found during weight download

Description (problem / solution / changelog)

Summary

Why this is not duplicating an existing PR

Test commands run and results

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Changed files

Code Example

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