update pretrained name

README.md

@@ -36,7 +36,8 @@ Notice, we removed the 'B-','I-' etc from data label.🗡
 ```python
 from transformers import pipeline
 
-ner = pipeline(task="ner",model="raynardj/ner-gene-gp", tokenizer="raynardj/ner-gene-gp")
+PRETRAINED = "raynardj/ner-gene-dna-rna-jnlpba-pubmed"
+ner = pipeline(task="ner",model=PRETRAINED, tokenizer=PRETRAINED)
 ner("Your text", aggregation_strategy="first")
 ```
 And here is to make your output more consecutive ⭐️
@@ -44,7 +45,7 @@ And here is to make your output more consecutive ⭐️
 ```python
 import pandas as pd
 from transformers import AutoTokenizer
-tokenizer = AutoTokenizer.from_pretrained("raynardj/ner-gene-gp")
+tokenizer = AutoTokenizer.from_pretrained(PRETRAINED)
 
 def clean_output(outputs):
     results = []
@@ -96,3 +97,7 @@ def entity_table(pipeline, **pipeline_kw):
 # will return a dataframe
 entity_table(ner)(YOUR_VERY_CONTENTFUL_TEXT)
 ```
+
+> check our NER model on
+* [gene and gene products](/raynardj/ner-gene-dna-rna-jnlpba-pubmed)
+* [chemical substance](/raynardj/ner-chemical-bionlp-bc5cdr-pubmed).