fix(llm-serving): clef-flash cannot run on a V100

The CLI path was wrong and is now correct, so the pod reaches the model loader — and
dies there:

  Found GPU0 Tesla V100-PCIE-32GB which is of cuda capability 7.0.
  Your installed torch==2.14.1+cu130 does not include kernels for this GPU.

Every GPU on worker-1 is a V100 (CC 7.0) and the pinned dev-clef image ships kernels for
CC 8.0 and above. Scale to zero so the pod stops crash-looping, and record the reason in
the manifest. Serving a 9.4B backbone on CPU is not a substitute.

k8s/apps/llm-serving/clef-flash.yaml

@@ -31,6 +31,17 @@ spec:
       # model class but would ignore the joint head and expose no systemone
       # endpoint, so it cannot serve this model correctly.
       #
+      # BLOCKED ON HARDWARE. worker-1 holds Tesla V100-PCIE-32GB cards, compute
+      # capability 7.0. The pinned image ships torch 2.14.1+cu130, whose kernels cover
+      # CC 8.0 and above only:
+      #
+      #   Found GPU0 Tesla V100-PCIE-32GB which is of cuda capability 7.0.
+      #   Your installed torch==2.14.1+cu130 does not include kernels for this GPU.
+      #
+      # So the pod starts and then dies in the model loader. minReplicas is 0 until
+      # either a build with sm_70 kernels exists or the model moves to newer hardware;
+      # serving it on CPU is not viable for a 9.4B backbone.
+      #
       # Image: the `dev-clef` tag is a pinned nightly because Clef support
       # landed after v0.5.21. Move to the official v0.5.22+ tag and re-pin by
       # digest when it ships; do not leave a nightly tag in git long term.
@@ -140,7 +151,8 @@ spec:
     deploymentStrategy:
       type: Recreate
     maxReplicas: 1
-    minReplicas: 1
+    # 0 until the hardware or the build changes: see the hardware note above.
+    minReplicas: 0
     nodeSelector:
       kubernetes.io/hostname: worker-1
     runtimeClassName: nvidia