examples : install torch-cpu for model conversion tool/example

[DamonFool]

I suggest adding --extra-index-url https://download.pytorch.org/whl/cpu in examples/model-conversion/requirements.txt.
Actually, we've done this in requirements-convert_hf_to_gguf.txt and some other requirements files.
Otherwise many nvidia dependents (see the following) would be required even on CPU-only machines, which would take a long time to download and waste disk space.

Collecting nvidia-cuda-nvrtc-cu12==12.4.127 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting nvidia-cuda-runtime-cu12==12.4.127 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting nvidia-cuda-cupti-cu12==12.4.127 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)
Collecting nvidia-cudnn-cu12==9.1.0.70 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)
Collecting nvidia-cublas-cu12==12.4.5.8 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting nvidia-cufft-cu12==11.2.1.3 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting nvidia-curand-cu12==10.3.5.147 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting nvidia-cusolver-cu12==11.6.1.9 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)
Collecting nvidia-cusparse-cu12==12.3.1.170 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)
Collecting nvidia-cusparselt-cu12==0.6.2 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_cusparselt_cu12-0.6.2-py3-none-manylinux2014_x86_64.whl.metadata (6.8 kB)
Collecting nvidia-nccl-cu12==2.21.5 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_nccl_cu12-2.21.5-py3-none-manylinux2014_x86_64.whl.metadata (1.8 kB)
Collecting nvidia-nvtx-cu12==12.4.127 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.7 kB)
Collecting nvidia-nvjitlink-cu12==12.4.127 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
Collecting triton==3.2.0 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading triton-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (1.4 kB)
Collecting sympy==1.13.1 (from torch~=2.6.0->-r requirements.txt (line 1))
  Downloading sympy-1.13.1-py3-none-any.whl.metadata (12 kB)

...

Downloading torch-2.6.0-cp310-cp310-manylinux1_x86_64.whl (766.7 MB)
   ━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 180.1/766.7 MB 9.2 MB/s eta 0:01:04

[DamonFool]

Thanks @danbev for your help.