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This repository was archived by the owner on May 29, 2026. It is now read-only.
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automated-interpretability
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neuron-explainer
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neuron_explainer
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activations
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token_connections.py
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main
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automated-interpretability
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neuron-explainer
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neuron_explainer
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activations
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token_connections.py
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from dataclasses import dataclass
from typing import List, Union
import blobfile as bf
from neuron_explainer.fast_dataclasses import FastDataclass, loads, register_dataclass
from neuron_explainer.azure import standardize_azure_url
import urllib.request
@register_dataclass
@dataclass
class TokensAndWeights(FastDataclass):
tokens: List[str]
strengths: List[float]
@register_dataclass
@dataclass
class WeightBasedSummaryOfNeuron(FastDataclass):
input_positive: TokensAndWeights
input_negative: TokensAndWeights
output_positive: TokensAndWeights
output_negative: TokensAndWeights
def load_token_weight_connections_of_neuron(
layer_index: Union[str, int],
neuron_index: Union[str, int],
dataset_path: str = "https://openaipublic.blob.core.windows.net/neuron-explainer/data/related-tokens/weight-based",
) -> WeightBasedSummaryOfNeuron:
"""Load the TokenLookupTableSummaryOfNeuron for the specified neuron."""
url = "/".join([dataset_path, str(layer_index), f"{neuron_index}.json"])
url = standardize_azure_url(url)
with urllib.request.urlopen(url) as f:
return loads(f.read(), backwards_compatible=False)
@register_dataclass
@dataclass
class TokenLookupTableSummaryOfNeuron(FastDataclass):
"""List of tokens and the average activations of a given neuron in response to each
respective token. These are selected from among the tokens in the vocabulary with the
highest average activations across an internet text dataset, with the highest activations
first."""
tokens: List[str]
average_activations: List[float]
def load_token_lookup_table_connections_of_neuron(
layer_index: Union[str, int],
neuron_index: Union[str, int],
dataset_path: str = "https://openaipublic.blob.core.windows.net/neuron-explainer/data/related-tokens/activation-based",
) -> TokenLookupTableSummaryOfNeuron:
"""Load the TokenLookupTableSummaryOfNeuron for the specified neuron."""
url = "/".join([dataset_path, str(layer_index), f"{neuron_index}.json"])
url = standardize_azure_url(url)
with urllib.request.urlopen(url) as f:
return loads(f.read(), backwards_compatible=False)
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