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import streamlit as st |
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import torch |
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import galai as gal |
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@st.cache_resource |
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def load_model(model_name): |
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model = gal.load_model(model_name, dtype=torch.float16) |
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return model |
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if 'text' not in st.session_state: |
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st.session_state['text'] = "" |
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def generate_text(): |
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st.session_state['text'] = model.generate(input_text=st.session_state.editor, penalty_alpha=penalty_alpha, top_k=top_k, max_new_tokens=max_new_tokens, new_doc=new_doc) |
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def suggest_reference(): |
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st.session_state['text'] = st.session_state.editor + " " + model.generate_reference(input_text=st.session_state.editor) |
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st.sidebar.markdown("### Select model") |
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choose_model = st.sidebar.selectbox("Size", ["mini", "base"]) |
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model = load_model(choose_model) |
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st.sidebar.markdown("### Text generation settings") |
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max_new_tokens = st.sidebar.slider("Max new tokens", value=60, min_value = 10, max_value = 200, step=10) |
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penalty_alpha = st.sidebar.slider("Alpha penalty", value = 0.6, min_value = 0.0, max_value=2.0, step=0.1) |
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top_k = st.sidebar.slider("Top-k", min_value = 0, max_value=10, value = 4) |
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new_doc = st.sidebar.checkbox("New document", value=True) |
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st.markdown( |
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''' |
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# Scientific writing assistant |
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## GALACTICA model |
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The [GALACTICA models](https://www.galactica.org) have been training on a large corpus of scientific data (see also the [GitHub repository](https://github.com/paperswithcode/galai)). Try out the two smaller models here and how they can be used to generate scientific text and suggest references. |
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Write text in the editor and push **TAB** or **CTRL+ENTER** to generate text. |
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Settings for model size (mini = 125 M and base = 1.3 B parameters) and text generation can be managed using from the left margin. |
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## Suggest citations |
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Use **Add citation** button to suggest and insert a citation into the text editor. The citation format is *Title, First author*. |
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''') |
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add_ref = st.button("Add citation", on_click=suggest_reference) |
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text_editor = st.text_area("(not shown)", st.session_state['text'], height = 500, key="editor", on_change=generate_text, label_visibility="collapsed") |
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