Update README.md

README.md

@@ -5,4 +5,28 @@ language:
 tags:
 - NLP
 pipeline_tag: feature-extraction
----
+---
+
+# Usage
+from transformers import AutoTokenizer
+from model import (
+    BERTContrastiveLearning_simcse,
+    BERTContrastiveLearning_simcse_w,
+    BERTContrastiveLearning_samp,
+    BERTContrastiveLearning_samp_w,
+)
+
+str_list = data["string"].tolist()  # Your list of strings here
+tokenizer = AutoTokenizer.from_pretrained("emilyalsentzer/Bio_ClinicalBERT")
+tokenized_inputs = tokenizer(
+    str_list, padding=True, max_length=50, truncation=True, return_tensors="pt"
+)
+input_ids = tokenized_inputs["input_ids"]
+attention_mask = tokenized_inputs["attention_mask"]
+
+model1 = BERTContrastiveLearning_simcse.load_from_checkpoint(ckpt1).eval()
+model2 = BERTContrastiveLearning_simcse_w.load_from_checkpoint(ckpt2).eval()
+model3 = BERTContrastiveLearning_samp.load_from_checkpoint(ckpt3).eval()
+model4 = BERTContrastiveLearning_samp_w.load_from_checkpoint(ckpt4).eval()
+
+cls, _ = model(input_ids, attention_mask)  # embeddings