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Transformers embedding Readme clarifications

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This commit is contained in:
Christian Tzolov
2023-11-10 08:05:47 +01:00
parent e423c3f127
commit 0a584f0dc2
1 changed files with 6 additions and 2 deletions
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8
embedding-clients/transformers-embedding/README.md
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@@ -59,6 +59,7 @@ TransformersEmbeddingClient embeddingClient = new TransformersEmbeddingClient();
// (optional) defaults to classpath:/onnx/all-MiniLM-L6-v2/tokenizer.json
embeddingClient.setTokenizerResource("classpath:/onnx/all-MiniLM-L6-v2/tokenizer.json");
// (optional) defaults to classpath:/onnx/all-MiniLM-L6-v2/model.onnx
embeddingClient.setModelResource("classpath:/onnx/all-MiniLM-L6-v2/model.onnx");
@@ -68,11 +69,14 @@ embeddingClient.setResourceCacheDirectory("/tmp/onnx-zoo");
embeddingClient.afterPropertiesSet();
List<List<Double>> embeddings =
embeddingClient.embed(List.of("Hello world", "World is big"));
List<List<Double>> embeddings = embeddingClient.embed(List.of("Hello world", "World is big"));
```
The first `embed()` call downloads the the large ONNX model and caches it on the local file system.
Therefore the first call might take longer than usual.
Use the `#setResourceCacheDirectory(<path>)` to set the local folder where the ONNX models as stored.
The default cache folder is `${java.io.tmpdir}/spring-ai-onnx-model`.