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Update Transformers.js example code (#4)

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- Update Transformers.js example code (ccf756833ba555e29e9b5b48288c2bf061ec8fda)


Co-authored-by: Joshua <Xenova@users.noreply.huggingface.co>

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  1. README.md +10 -4
README.md CHANGED
@@ -2733,14 +2733,20 @@ The model natively supports scaling of the sequence length past 2048 tokens. To
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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', {
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  quantized: false, // Comment out this line to use the quantized version
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  });
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  // Compute sentence embeddings
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- const texts = ['What is TSNE?', 'Who is Laurens van der Maaten?'];
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- const embeddings = await extractor(texts, { pooling: 'mean', normalize: true });
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- console.log(embeddings);
 
 
 
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  ```
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  # Join the Nomic Community
 
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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', {
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  quantized: false, // Comment out this line to use the quantized version
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  });
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+ // Define sentences
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+ const texts = ['search_query: What is TSNE?', 'search_query: Who is Laurens van der Maaten?'];
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+
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  // Compute sentence embeddings
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+ let embeddings = await extractor(texts, { pooling: 'mean' });
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+ console.log(embeddings); // Tensor of shape [2, 768]
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+
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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