update app
Browse files
app.py
CHANGED
@@ -3,7 +3,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
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from transformers import pipeline
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import torch
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import json
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-
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@st.cache(allow_output_mutation=True)
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def load_tokenizer(model_ckpt):
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@@ -59,16 +59,19 @@ set_seed(42)
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gen_kwargs = {}
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if selected_task == " ":
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st.title("Code Generation Models comparison
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with open("intro.txt", "r") as f:
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intro = f.read()
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st.markdown(intro)
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elif selected_task == "Pretraining dataset":
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st.title("Pretraining datasets π")
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for model in selected_models:
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with open(f"datasets/{model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(f"
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st.markdown(text)
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elif selected_task == "Model architecture":
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st.title("Model architecture π¨")
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from transformers import pipeline
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import torch
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import json
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import pandas as pd
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@st.cache(allow_output_mutation=True)
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def load_tokenizer(model_ckpt):
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gen_kwargs = {}
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if selected_task == " ":
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st.title("Code Generation Models comparison")
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with open("intro.txt", "r") as f:
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intro = f.read()
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st.markdown(intro)
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elif selected_task == "Pretraining dataset":
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st.title("Pretraining datasets π")
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st.Markdown("Preview of some code files from Github repositories")
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df = pd.read_csv("preview-github-data.csv")
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st.dataframe(df)
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for model in selected_models:
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with open(f"datasets/{model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(f"### {model}:")
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st.markdown(text)
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elif selected_task == "Model architecture":
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st.title("Model architecture π¨")
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