Update README.md

README.md

@@ -39,3 +39,36 @@ The following hyperparameters were used during training:
 - Pytorch 1.10.1+cu102
 - Datasets 1.17.0
 - Tokenizers 0.11.0
+
+## Usage (HuggingFace Transformers)
+You can use the model like this: 
+
+```python
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+# label_list
+label_list = ['matched', 'unmatched']
+
+# Load model from HuggingFace Hub
+tokenizer = AutoTokenizer.from_pretrained("Fan-s/reddit-tc-bert", use_fast=True)
+model = AutoModelForSequenceClassification.from_pretrained("Fan-s/reddit-tc-bert") 
+
+# set the input
+post = "don't make gravy with asbestos."
+response = "i'd expect someone with a culinary background to know that. since we're talking about school dinner ladies, they need to learn this pronto."
+
+def predict(post, response, max_seq_length=128):
+    with torch.no_grad():
+        args =  (post, response)
+        input = tokenizer(*args, padding="max_length", max_length=max_seq_length, truncation=True, return_tensors="pt")
+        output = model(**input)
+        logits = output.logits
+        item = torch.argmax(logits, dim=1)
+        predict_label = label_list[item]
+        return predict_label, logits
+
+# predict whether the two sentences match                 
+predict_label = predict(post, response)
+print("predict_label:", predict_label)
+```