Core ML: accept a sequence length of 1

The published build rejected seq=1 with "Size (1) of dimension (1) is not in
allowed range (2..74)", which surfaced in React Native ExecuTorch as
Error::DelegateInvalidHandle for any single-word input. See
software-mansion/react-native-executorch#1164.

torch.export keeps the declared min of 1; to_edge_transform_and_lower is what
widened the token dim to 2..74. Exporting under
torch.fx.experimental._config.backed_size_oblivious keeps 1 in the range.
schema.json already declared min 1, so the file now matches the contract it
publishes rather than the other way round.

Verified on macOS (ExecuTorch 1.4.1) against the eager model, cosine at every
length from 1 to the maximum:

seq=1 0.99998
seq=2 0.99997
seq=16 0.99990
seq=74 0.99991

and on an iPhone 16 in the demo app, where a single word now embeds instead of
failing.

The file name is unchanged, so nothing moves in the model registry.

coreml/clip_vit_base_patch32_text_coreml_fp16.pte

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7be060864a0d48002dfdab28b2927a8c4ef467bfb5a3a95a8093ec4b3327c0b9
+oid sha256:16a5012e115d79121ab7ccc0204f983e9909dc1f12126a7f4fe4dd217c56d5ed
 size 127415056