Add layer norm usage for Transformers.js

#11
by Xenova HF staff - opened
Files changed (1) hide show
  1. README.md +5 -3
README.md CHANGED
@@ -2730,7 +2730,7 @@ The model natively supports scaling of the sequence length past 2048 tokens. To
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  ### Transformers.js
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  ```js
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- import { pipeline } from '@xenova/transformers';
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  // Create a feature extraction pipeline
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  const extractor = await pipeline('feature-extraction', 'nomic-ai/nomic-embed-text-v1.5', {
@@ -2745,8 +2745,10 @@ let embeddings = await extractor(texts, { pooling: 'mean' });
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  console.log(embeddings); // Tensor of shape [2, 768]
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  const matryoshka_dim = 512;
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- embeddings = embeddings.slice(null, [0, matryoshka_dim]).normalize(2, -1);
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- console.log(embeddings); // Tensor of shape [2, 512]
 
 
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  ```
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  # Join the Nomic Community
 
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  ### Transformers.js
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  ```js
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+ import { pipeline, layer_norm } from '@xenova/transformers';
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  // Create a feature extraction pipeline
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  const extractor = await pipeline('feature-extraction', 'nomic-ai/nomic-embed-text-v1.5', {
 
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  console.log(embeddings); // Tensor of shape [2, 768]
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  const matryoshka_dim = 512;
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+ embeddings = layer_norm(embeddings, [embeddings.dims[1]])
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+ .slice(null, [0, matryoshka_dim])
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+ .normalize(2, -1);
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+ console.log(embeddings.tolist());
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  ```
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  # Join the Nomic Community