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AQIT 0.1.0
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Go to the source code of this file.
Namespaces | |
| namespace | aquin |
| namespace | aquin.compute |
| namespace | aquin.compute.interp_score |
Functions | |
| dict | aquin.compute.interp_score._generate_sentences (str label, client, int n=N_SAMPLES) |
| float | aquin.compute.interp_score._get_feature_activation (str sentence, int feature_idx, HookedTransformer model, SparseAutoencoder sae, str model_id="llama-3.2-1b", int|None layer=None) |
| float | aquin.compute.interp_score._cohen_d_score (list[float] pos_acts, list[float] neg_acts) |
| float|None | aquin.compute.interp_score._feature_purity_score (list[str] sentences, client) |
| float|None | aquin.compute.interp_score._finite (float|None x, float|None default=None) |
| float | aquin.compute.interp_score._kl_div (torch.Tensor p, torch.Tensor q) |
| float | aquin.compute.interp_score._entropy (torch.Tensor p) |
| dict | aquin.compute.interp_score.run_mui_score (int feature_idx, str prompt, HookedTransformer model, SparseAutoencoder sae, int n_positions=8, str model_id="llama-3.2-1b", int|None layer=None) |
| dict | aquin.compute.interp_score.run_interp_score (int feature_idx, str prompt, HookedTransformer model, SparseAutoencoder sae, client, int n_samples=N_SAMPLES, str model_id="llama-3.2-1b", int|None layer=None) |
Variables | |
| aquin.compute.interp_score.DEVICE = resolve_compute_device() | |
| int | aquin.compute.interp_score.N_SAMPLES = 10 |