Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 license: apache-2.0
 ---
-# Cross-Encoder for Quora Duplicate Questions Detection
+# Cross-Encoder for SQuAD (QNLI)
 This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
 
 ## Training Data
@@ -15,7 +15,8 @@ For performance results of this model, see [SBERT.net Pre-trained Cross-Encoder]
 Pre-trained models can be used like this:
 ```python
 from sentence_transformers import CrossEncoder
-model = CrossEncoder('model_name')
+
+model = CrossEncoder('cross-encoder/qnli-distilroberta-base')
 scores = model.predict([('Query1', 'Paragraph1'), ('Query2', 'Paragraph2')])
 
 #e.g.
@@ -28,8 +29,8 @@ You can use the model also directly with Transformers library (without SentenceT
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 
-model = AutoModelForSequenceClassification.from_pretrained('model_name')
-tokenizer = AutoTokenizer.from_pretrained('model_name')
+model = AutoModelForSequenceClassification.from_pretrained('cross-encoder/qnli-distilroberta-base')
+tokenizer = AutoTokenizer.from_pretrained('cross-encoder/qnli-distilroberta-base')
 
 features = tokenizer(['How many people live in Berlin?', 'What is the size of New York?'], ['Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.', 'New York City is famous for the Metropolitan Museum of Art.'],  padding=True, truncation=True, return_tensors="pt")