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README.md

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+---
+base_model:
+- google-bert/bert-base-uncased
+---
+# 🔍 BERT Token Classification – Important Chunk Extractor (ONNX)
+
+This model identifies and extracts important parts of input sentences using BERT-based token classification, exported to the ONNX format for optimized inference.
+---
+## 🧠 Use Case
+This model is designed for **context engineering** — to extract semantically important words or chunks from sentences or chat messages, enabling better personalization in downstream applications like AI assistants or dialogue systems.
+
+Example:
+```text
+Input:  I’ll be unavailable tomorrow due to a team offsite.
+Output: [unavailable, tomorrow, team offsite]
+````
+---
+
+## 🛠️ Model Details
+* **Architecture**: BERT (`bert-base-uncased`) fine-tuned for token classification
+* **Exported to**: ONNX for efficient runtime inference via [Optimum](https://huggingface.co/docs/optimum/onnxruntime)
+* **Labels**:
+
+  * `0`: Not Important
+  * `1`: Important
+---
+
+## 📦 How to Use (with 🤗 Transformers + Optimum)
+```python
+from transformers import AutoTokenizer
+from optimum.onnxruntime import ORTModelForTokenClassification
+import torch
+
+model = ORTModelForTokenClassification.from_pretrained("your-username/bert-token-onnx", file_name="model.onnx")
+tokenizer = AutoTokenizer.from_pretrained("your-username/bert-token-onnx")
+
+text = "The server will go down at midnight for maintenance."
+
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model(**inputs)
+predictions = torch.argmax(outputs.logits, dim=-1)
+
+tokens = tokenizer.convert_ids_to_tokens(inputs["input_ids"][0])
+important_tokens = [tok for tok, label in zip(tokens, predictions[0]) if label == 1]
+print("Important tokens:", important_tokens)
+```
+---
+
+## 📁 Files Included
+| File                      | Purpose                             |
+| ------------------------- | ----------------------------------- |
+| `model.onnx`              | Exported ONNX model                 |
+| `config.json`             | Model config                        |
+| `tokenizer_config.json`   | Tokenizer config                    |
+| `vocab.txt`               | Vocabulary for BERT tokenizer       |
+| `special_tokens_map.json` | Tokenization map for special tokens |
+| `README.md`               | Model usage documentation           |