Update README.md

README.md

@@ -76,11 +76,11 @@ Can be easily integrated into your existing spaCy-based NLP pipelines.
 
 
 ### Usage
-Installation
-You can install the custom spaCy NER model using pip:
+#### Installation
+##### You can install the custom spaCy NER model using pip:
 
 ```bash
-Copy code
+
 pip install https://huggingface.co/DaFull/en_ner_job_postings/resolve/main/en_ner_job_postings-any-py3-none-any.whl
 
 ```
@@ -99,18 +99,18 @@ text = "HR Specialist needed at XYZ Corporation, Dallas, TX, with expertise in e
 doc = nlp(text)
 
 # Extract named entities
-'for ent in doc.ents:
+for ent in doc.ents:
     print(f"Entity: {ent.text}, Type: {ent.label_}")
 
 ```
 
-Entity Types
+####  Entity Types
 The model recognizes the following entity types:
 
-PROFESSION: Represents professions or job titles.
-FACILITY: Denotes facilities, buildings, or locations.
-EXPERIENCE: Identifies mentions of work experience, durations, or qualifications.
-'
+- PROFESSION: Represents professions or job titles.
+- FACILITY: Denotes facilities, buildings, or locations.
+- EXPERIENCE: Identifies mentions of work experience, durations, or qualifications.
+
 ### Label Scheme
 
 <details>