Update README.md

README.md

@@ -9,6 +9,33 @@ This is an embedding model for clinical papers
 
 ## How to Use
 
+### Simple finetuned model
+
+```python
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+DEVICE = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+PATH = "josh-oo/aspect-based-embeddings-v3"
+
+tokenizer = AutoTokenizer.from_pretrained(PATH)
+model = AutoModel.from_pretrained(PATH)
+
+dummy_text = "This is a title of a medical paper"
+dummy_input = tokenizer([dummy_text], return_tensors="pt")
+
+dummy_input.to(DEVICE)
+model.to(DEVICE)
+
+with torch.no_grad():
+  output = model(**dummy_input)
+
+embeddings = output.last_hidden_state[:, 0] #cls pooling
+```
+
+### Aspect guided model
+
 ```python
 from transformers import AutoTokenizer, AutoModel
 import torch
@@ -36,5 +63,5 @@ model.to(DEVICE)
 with torch.no_grad():
   output = model(**dummy_input)
 
-embeddings = output.last_hidden_state[:, 0]
+embeddings = output.last_hidden_state[:, 0] #cls pooling
 ```