Document the preflight check

README.md

@@ -224,7 +224,21 @@ on PyPI is now a cu130 build and cu130 dropped Volta. Measured on a V100:
 
 That failure arrives at the *first kernel launch*, well after
 `torch.cuda.is_available()` has returned `True`, so it does not look like an
-installation problem. On sm_70 install a cu128 build:
+installation problem — which is why **the loader checks first**. Before reading
+a byte of the 8.46 GB it compares your card against
+`torch.cuda.get_arch_list()` and, on a mismatch, stops with the fix:
+
+```
+this torch (2.13.0+cu130) has no kernels for Tesla V100-SXM2-16GB (sm_70).
+It was built for sm_75, sm_80, sm_86, sm_90, sm_100, sm_120, and the first CUDA
+op would fail with 'no kernel image is available for execution on the device'.
+The model is fine - it needs no custom kernels. Install a torch built for your
+card, e.g. for sm_70:
+  pip install torch --index-url https://download.pytorch.org/whl/cu128
+or pass device='cpu' to load without touching the GPU.
+```
+
+On sm_70 install a cu128 build:
 
 ```bash
 pip install torch --index-url https://download.pytorch.org/whl/cu128