Update README.md

README.md

@@ -8,6 +8,29 @@ tags:
 license: mit
 ---
 
+```python
+import onnxruntime as ort
+import numpy as np
+from transformers import AutoTokenizer
+from huggingface_hub import hf_hub_download
+
+# ── Load ───────────────────────────────────────────────────────────────────
+tokenizer    = AutoTokenizer.from_pretrained("alanjoshua2005/text-embedding", subfolder="tokenizer")
+onnx_path    = hf_hub_download("alanjoshua2005/text-embedding", "onnx/biencoder_rope.onnx")
+session      = ort.InferenceSession(onnx_path, providers=["CPUExecutionProvider"])
+
+# ── Encode ─────────────────────────────────────────────────────────────────
+def encode(texts):
+    if isinstance(texts, str): texts = [texts]
+    enc = tokenizer(texts, padding=True, truncation=True, max_length=256, return_tensors="np")
+    return session.run(["embeddings"], {"input_ids": enc["input_ids"], "attention_mask": enc["attention_mask"]})[0]
+
+# ── Test ───────────────────────────────────────────────────────────────────
+emb = encode("Hello world!")
+print(emb)   # (1, 256)
+```
+
+
 # BiEncoder RoPE — Sentence Embedding Model
 
 A 34M parameter sentence embedding model trained from scratch using PyTorch.