Update src/app.py

src/app.py

@@ -34,9 +34,6 @@ model_list = [
     "tiiuae/falcon-40B-Instruct",
     "tiiuae/falcon-180B",
     "tiiuae/falcon-180B-Chat",
-    "google/gemma-7b",
-    "google/gemma-2b",
-    "abacusai/TheProfessor-155b",
 ]
 st.title("Lambda LLM VRAM Calculator")
 
@@ -124,7 +121,7 @@ with col.expander("Detailed Information", expanded=False):
     st.markdown("""- For LoRa Fine-tuning, This assumes a **16-bit** dtype of trainable parameters. The formula (in terms of GB) is""")
     st.latex(r"\text{Memory}_\text{LoRa} \approx \text{Model Size} + \left(\text{ \# trainable Params}_\text{Billions}\times\frac{16}{8} \times 4\right) \times 1.2")
 
-access_token = st.sidebar.text_input("Access token")
+# access_token = st.sidebar.text_input("Access token")
 
 # if access_token:
 #    login(token=access_token)