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Improve transformers embedding readme

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Christian Tzolov
2023-11-10 00:22:14 +01:00
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embedding-clients/transformers-embedding/README.md
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@@ -14,7 +14,7 @@ To run things in Java, we need to serialize the Tokenizer and the Transformer Mo
One, quick, way to achieve this, is to use the [optimum-cli](https://huggingface.co/docs/optimum/exporters/onnx/usage_guides/export_a_model#exporting-a-model-to-onnx-using-the-cli) command line tool.
Following snippet creates an python virtual environment, installs the required packages and runs the optimum-cli to serialize (e.g. export) the models:
Following snippet prepares a python virtual environment, installs the required packages and serializes (e.g. exports) specified model using `optimum-cli` :
```bash
python3 -m venv venv
@@ -24,14 +24,25 @@ source ./venv/bin/activate
(venv) optimum-cli export onnx --model sentence-transformers/all-MiniLM-L6-v2 onnx-output-folder
```
The `optimum-cli` command exports the [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) transformer into the `onnx-output-folder` folder. Later includes the `tokenizer.json` and `model.onnx` files used by the embedding client.
The snippet exports the [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) transformer into the `onnx-output-folder` folder. Later includes the `tokenizer.json` and `model.onnx` files used by the embedding client.
## Apply the ONNX model
In place of the all-MiniLM-L6-v2 you can pick any huggingface transformer identifier or provide direct file path.
Use the `setTokenizerResource(tokenizerJsonUri)` and `setModelResource(modelOnnxUri)` methods to set the URI locations of the exported `tokenizer.json` and `model.onnx` files.
The `classpath:`, `file:` or `https:` URI schemas are supported.
## Using the ONNX models
If no other model is explicitly set, the `TransformersEmbeddingClient` defaults to [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) model:
Add the `transformers-embedding` project to your maven dependencies:
```xml
<dependency>
<groupId>org.springframework.experimental.ai</groupId>
<artifactId>transformers-embedding</artifactId>
<version>0.7.0-SNAPSHOT</version>
</dependency>
```
then create a new `TransformersEmbeddingClient` instance and use the `setTokenizerResource(tokenizerJsonUri)` and `setModelResource(modelOnnxUri)` methods to set the URIs of the exported `tokenizer.json` and `model.onnx` files. (`classpath:`, `file:` or `https:` URI schemas are supported).
If the model is not explicitly set, `TransformersEmbeddingClient` defaults to [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2):
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