update readme

Signed-off-by: [email protected] <[email protected]>

README.md

@@ -21688,6 +21688,37 @@ embeddings = model.encode(
 )
 ```
 
+Furthermore, you can use ONNX for efficient inference with `jina-embeddings-v3`:
+```python
+import onnxruntime
+import numpy as np
+from transformers import AutoTokenizer, PretrainedConfig
+
+# Load tokenizer and model config
+tokenizer = AutoTokenizer.from_pretrained('jinaai/jina-embeddings-v3')
+config = PretrainedConfig.from_pretrained('jinaai/jina-embeddings-v3')
+
+# Tokenize input
+input_text = tokenizer('sample text', return_tensors='np')
+
+# ONNX session
+model_path = 'jina-embeddings-v3/onnx/model.onnx'
+session = onnxruntime.InferenceSession(model_path)
+
+# Prepare inputs for ONNX model
+task_type = 'text-matching'
+task_id = np.array(config.lora_adaptations.index(task_type), dtype=np.int64)
+inputs = {
+    'input_ids': input_text['input_ids'],
+    'attention_mask': input_text['attention_mask'],
+    'task_id': task_id
+}
+
+# Run model
+outputs = session.run(None, inputs)
+```
+
+
 
 
 ## Performance