Update app.py

app.py

@@ -7,6 +7,7 @@ import torch
 model_checkpoint = "vives/distilbert-base-uncased-finetuned-cvent-2022"
 model = AutoModelForMaskedLM.from_pretrained(model_checkpoint,output_hidden_states=True)
 model_base = AutoModelForMaskedLM.from_pretrained("distilbert-base-uncased", output_hidden_states=True)
+model_2019_2022 = AutoModelForMaskedLM.from_pretrained("vives/distilbert-base-uncased-finetuned-cvent-2019_2022",output_hidden_states=True)
 tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
 text1 = st.text_area("Enter first sentence")
 text2 = st.text_area("Enter second sentence")
@@ -54,5 +55,12 @@ if text1 and text2:
         mean_pooled_base[1:]
     )[0][0]
     
-    st.write(f">>>Similarity for fine-tuned {fine_tuned_out}")
+    outputs_2019_2022 = model_2019_2022(**tokens)
+    mean_pooled_2019_2022 = pool_embeddings(outputs_2019_2022,tokens).detach().numpy()
+    fine_tuned_out2 = cosine_similarity(
+        [mean_pooled_2019_2022[0]],
+        mean_pooled_2019_2022[1:]
+    )[0][0]
+    st.write(f">>>Similarity for fine-tuned (2022) {fine_tuned_out}")
+    st.write(f">>>Similarity for fine-tuned (2019-2022) {fine_tuned_out}")
     st.write(f">>>Similarity for base {base_out}")