Update src/app.py
Browse files- src/app.py +1 -4
src/app.py
CHANGED
@@ -34,9 +34,6 @@ model_list = [
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"tiiuae/falcon-40B-Instruct",
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"tiiuae/falcon-180B",
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"tiiuae/falcon-180B-Chat",
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"google/gemma-7b",
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"google/gemma-2b",
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"abacusai/TheProfessor-155b",
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]
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st.title("Lambda LLM VRAM Calculator")
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@@ -124,7 +121,7 @@ with col.expander("Detailed Information", expanded=False):
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st.markdown("""- For LoRa Fine-tuning, This assumes a **16-bit** dtype of trainable parameters. The formula (in terms of GB) is""")
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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")
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access_token = st.sidebar.text_input("Access token")
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# if access_token:
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# login(token=access_token)
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"tiiuae/falcon-40B-Instruct",
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"tiiuae/falcon-180B",
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"tiiuae/falcon-180B-Chat",
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]
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st.title("Lambda LLM VRAM Calculator")
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st.markdown("""- For LoRa Fine-tuning, This assumes a **16-bit** dtype of trainable parameters. The formula (in terms of GB) is""")
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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")
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+
# access_token = st.sidebar.text_input("Access token")
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# if access_token:
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# login(token=access_token)
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