Update README.md

README.md

@@ -15,7 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 # ParsBERT-nli-FarsTail-FarSick
 
-This model is a fine-tuned version of [HooshvareLab/bert-fa-zwnj-base](https://huggingface.co/HooshvareLab/bert-fa-zwnj-base) on the None dataset.
+This model is a fine-tuned version of [HooshvareLab/bert-fa-zwnj-base](https://huggingface.co/HooshvareLab/bert-fa-zwnj-base) on the [FarsTail](https://github.com/dml-qom/FarsTail/tree/master)
+ and [FarSick](https://github.com/ZahraGhasemi-AI/FarSick/tree/main) datasets.
 It achieves the following results on the evaluation set:
 - Loss: 0.8730
 - Accuracy: 0.8055
@@ -29,7 +30,20 @@ It achieves the following results on the evaluation set:
 ## How to use
 
 ``` python
+import torch
+import transformers
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
+model_name_or_path = "parsi-ai-nlpclass/ParsBERT-nli-FarsTail-FarSick"
+config = transformers.AutoConfig.from_pretrained(model_name_or_path)
+tokenizer_pb = transformers.AutoTokenizer.from_pretrained(model_name_or_path)
+model_pb = transformers.AutoModelForSequenceClassification.from_pretrained(model_name_or_path,
+                                                                           num_labels=3)
+premise = "سلام خوبی؟"
+hypothesis = "آره خوبم"
+print(model_pb(**tokenizer_pb(premise, hypothesis, return_tensors='pt')))
+
+model_pb.to(device)
 ```
 
 ### Training hyperparameters