Add usage details

README.md

@@ -20,7 +20,66 @@ model-index:
     - name: NER F Score
       type: f_score
       value: 0.9899159664
+license: mit
 ---
+### Details: https://github.com/JackLeeJM/slm-medication-ner
+
+### Usage
+
+1. Install using PIP:
+  ```bash
+  !pip install "en_spacy_medication_ner @ https://huggingface.co/jackleejm/en_spacy_medication_ner/resolve/main/en_spacy_medication_ner-any-py3-none-any.whl"
+  ```
+2. Load model:
+  ```python
+  import spacy
+
+  nlp = spacy.load("en_spacy_medication_ner")
+  ```
+3. Run inferences:
+  ```python
+  input = ["Acetaminophen 325 MG Oral Tablet"]
+  docs = list(nlp.pipe(input))
+  results = [
+    [
+      {
+        "word": ent.text,
+        "entity_group": ent.label_,
+        "start": ent.start_char,
+        "end": ent.end_char,
+      }
+      for ent in doc.ents
+    ]
+    for doc in docs
+  ]
+
+  print(results)
+
+  # Outputs
+  [
+    [
+      {
+        "word": "Acetaminophen",
+        "entity_group": "DRUG",
+        "start": 0,
+        "end": 13
+      },
+      {
+        "word": "325 MG",
+        "entity_group": "DOSAGE",
+        "start": 14,
+        "end": 20
+      },
+      {
+        "word": "Oral Tablet",
+        "entity_group": "ROUTE",
+        "start": 21,
+        "end": 32
+      }
+    ]
+  ]
+  ```
+
 | Feature | Description |
 | --- | --- |
 | **Name** | `en_spacy_medication_ner` |
@@ -30,8 +89,8 @@ model-index:
 | **Components** | `tok2vec`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 | **Sources** | n/a |
-| **License** | n/a |
-| **Author** | [n/a]() |
+| **License** | MIT |
+| **Author** | [JackLeeJM](https://github.com/JackLeeJM) |
 
 ### Label Scheme