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README.md

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-license: apache-2.0
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+# Gene Extraction Model
+
+This model is fine-tuned for gene extraction using BERT-CRF architecture.
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
+
+# Load model and tokenizer
+model_name = "RaduGabriel/gene-entity-recognition"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForTokenClassification.from_pretrained(model_name)
+
+# Create NER pipeline
+ner_pipeline = pipeline(
+    "ner",
+    model=model,
+    tokenizer=tokenizer,
+    aggregation_strategy="simple"
+)
+
+# Example usage
+text = "The BRCA1 gene is associated with breast cancer."
+results = ner_pipeline(text)
+```
+
+## Labels
+- O
+- B-GENE
+- I-GENE
+- E-GENE
+- S-GENE
+
+## Model Details
+- Architecture: BERT-CRF
+- Base Model: answerdotai/ModernBERT-large
+- Number of Labels: 5
+- CRF Layer: Enabled