Update README.md

README.md

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-license: mit
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+---
+license: mit
+---
+---
+language: en
+license: apache-2.0
+---
+
+# My BERT Model
+
+This is a BERT model fine-tuned for extracting embeddings from CVs and startup descriptions for matching purposes.
+
+## Model Details
+
+- **Architecture:** BERT-base-uncased
+- **Use case:** CV and Startup matching
+- **Training data:** Not applicable (pre-trained model used)
+
+## How to use
+
+```python
+from transformers import BertTokenizer, BertModel
+
+tokenizer = BertTokenizer.from_pretrained("your_username/your_model_name")
+model = BertModel.from_pretrained("your_username/your_model_name")
+
+text = "Sample text"
+inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+outputs = model(**inputs)
+embedding = outputs.last_hidden_state.mean(dim=1).detach().numpy()