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Feature Extraction — Recording the Evidence

After training (or downloading an external SAE), run an Extraction Job to scan your dataset and record which features activate on which tokens.

Extraction Panel — Completed extraction jobs

Extraction Configuration

miStudio supports two extraction types: Feature Extraction (from a trained SAE) and Activation Extraction (raw activations for training).

Feature Extraction Configuration

Feature Extraction Job Configuration — SAE selection and parameters

Feature Extraction Job Configuration — Token filtering and context

Activation Extraction Configuration

Activation Extraction Job Configuration

ParameterDefaultRangeDescription
Evaluation Samples10,000100–1,000,000Dataset samples to scan. More = better coverage but slower.
Top-K Examples10010–1,000Max-activating examples saved per feature. More = richer context for labeling.
Batch SizeAuto8–256Processing batch size. Auto-detected based on available VRAM.

Token Filtering

Control which tokens appear in activation examples. These filters affect both extraction and labeling:

FilterDefaultEffect
Special Tokens✅ OnRemoves <s>, </s>, <pad>, etc.
Single Characters✅ OnRemoves single-character tokens
Punctuation✅ OnRemoves pure punctuation tokens
Numbers✅ OnRemoves pure numeric tokens
Fragments✅ OnRemoves BPE subwords like "tion", "ing"
Stop Words❌ OffOptionally removes "the", "and", "is", etc.
Filter Strategy

Keep most filters ON for cleaner labeling results. Only disable fragment filtering if you're specifically studying tokenization patterns. Enable stop word filtering when you want labels focused on content words.

Context Window

Each activation example includes surrounding context for interpretation:

SettingDefaultDescription
Prefix Tokens25Tokens shown before the activating token
Suffix Tokens25Tokens shown after the activating token

The asymmetric window (25+25=50 tokens of context) is based on research showing this window size captures sufficient context for accurate labeling.

Dead Feature Filtering

Features that activate too rarely are filtered:

SettingDefaultDescription
Min Activation Frequency0.001 (0.1%)Features firing less than this rate are excluded as "dead"

Browsing Extracted Features

Once extraction completes, browse the discovered features in the feature browser:

Feature Browser — Browsing extracted features with labels and statistics

Click any feature to view its activation examples, token context, and detailed statistics:

Feature Details — Activation examples and token-level analysis