Add layer norm usage for Transformers.js

Relevant discussion: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5/discussions/4#65cce8d0c52afc14ceac26c2

README.md

@@ -2730,7 +2730,7 @@ The model natively supports scaling of the sequence length past 2048 tokens. To
 ### Transformers.js
 
 ```js
-import { pipeline } from '@xenova/transformers';
+import { pipeline, layer_norm } from '@xenova/transformers';
 
 // Create a feature extraction pipeline
 const extractor = await pipeline('feature-extraction', 'nomic-ai/nomic-embed-text-v1.5', {
@@ -2745,8 +2745,10 @@ let embeddings = await extractor(texts, { pooling: 'mean' });
 console.log(embeddings); // Tensor of shape [2, 768]
 
 const matryoshka_dim = 512;
-embeddings = embeddings.slice(null, [0, matryoshka_dim]).normalize(2, -1);
-console.log(embeddings); // Tensor of shape [2, 512]
+embeddings = layer_norm(embeddings, [embeddings.dims[1]])
+    .slice(null, [0, matryoshka_dim])
+    .normalize(2, -1);
+console.log(embeddings.tolist());
 ```
 
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