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82138fc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | from __future__ import annotations
from pathlib import Path
import gradio as gr
import pandas as pd
import plotly.graph_objects as go
DATA = pd.read_parquet(
Path(__file__).resolve().parent / "data" / "feature_exemplars.parquet"
)
FEATURES = sorted(DATA["feature"].unique().tolist())
def inspect_feature(feature: int) -> tuple[go.Figure, dict]:
feature = int(feature)
rows = DATA[DATA["feature"] == feature].sort_values("rank")
figure = go.Figure(
go.Bar(
x=rows["token"].tolist(),
y=rows["activation"].tolist(),
marker_color="#a78bfa",
customdata=rows["token_id"].tolist(),
hovertemplate="token=%{x}<br>id=%{customdata}<br>activation=%{y:.3f}",
)
)
figure.update_layout(
title=f"Feature {feature}: top held-out token activations",
xaxis_title="BPE token",
yaxis_title="Sparse feature activation",
template="plotly_dark",
)
return figure, {
"feature": feature,
"heldout_firing_rate": round(float(rows["firing_rate"].iloc[0]), 6),
"top_tokens": rows["token"].tolist(),
"warning": "Token exemplars are clues, not causal concept labels.",
}
with gr.Blocks(title="SNIP Scope") as demo:
gr.Markdown(
"# SNIP Scope\n"
"Explore top held-out token activations for 384 sparse features learned "
"from the SNIP transformer's final hidden layer."
)
feature = gr.Slider(0, max(FEATURES), 0, step=1, label="Sparse feature")
run = gr.Button("Inspect feature", variant="primary")
exemplars = gr.Plot()
details = gr.JSON()
run.click(inspect_feature, feature, [exemplars, details])
demo.load(inspect_feature, feature, [exemplars, details])
if __name__ == "__main__":
demo.launch()
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