Update README.md

README.md

@@ -18,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # clinical-ner
 
-This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the Medical dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.8058
 - Precision: 0.5786
@@ -55,6 +55,22 @@ The following hyperparameters were used during training:
 - num_epochs: 45
 - mixed_precision_training: Native AMP
 
+### Python Code:
+```python
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+pipe = pipeline("token-classification", model="Clinical-AI-Apollo/Medical-NER", aggregation_strategy='simple')
+result = pipe('45 year old woman diagnosed with CAD')
+
+
+
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("Clinical-AI-Apollo/Medical-NER")
+model = AutoModelForTokenClassification.from_pretrained("Clinical-AI-Apollo/Medical-NER")
+```
+
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |