probe-inference weights

Trained activation probes in four architectures (linear, MLP, EFC (early-fusion covariance) and axial) for seven open-weight models. Each probe reads a model's residual-stream activations at six decoder layers and returns one score per transcript. Load them with the probe-inference package:

from probe_inference import load_probe_from_hub

probe = load_probe_from_hub("qwen3.5-9b/efc")  # this repository at the package's pinned revision
score = probe.score(acts, probe.read_mask(prompt_mask, completion_mask, followup_start_position))

Layout

<model>/<arch>/, with <arch> in linear, mlp, efc, axial. Each directory is one trained probe. A linear or MLP probe is one small probe per layer (layer_<L>/config.json, layer_<L>/model.pt); an EFC or axial probe is one module that reads all its layers at once (config.json, model.pt). Every probe has probe_metadata.json: the model and revision, the layers, the read window (obfuscate_over), the token aggregation and, for linear and MLP, the layers whose sigmoids are averaged (layer_rule.used_layers). model.pt files are plain float32 state dicts.

Directory Model (revision) Layers linear MiB MLP MiB EFC MiB axial MiB
qwen3.5-2b Qwen/Qwen3.5-2B (15852e8c) 7, 10, 13, 16, 19, 22 0.1 12.0 6.1 26.1
qwen3.5-9b Qwen/Qwen3.5-9B (c2022362) 10, 13, 18, 21, 26, 29 0.1 24.0 12.1 28.1
qwen3.6-27b Qwen/Qwen3.6-27B (6a9e13bd) 19, 27, 35, 43, 51, 58 0.1 30.0 15.1 29.2
qwen3.5-122b-a10b Qwen/Qwen3.5-122B-A10B (dc4d3484) 14, 20, 26, 32, 38, 43 0.1 18.0 9.1 27.1
qwen3.5-397b-a17b Qwen/Qwen3.5-397B-A17B (84726181) 18, 25, 33, 40, 48, 54 0.1 24.0 12.1 28.1
nemotron-3-nano-30b-a3b nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 (bf77c317) 16, 22, 29, 35, 42, 47 0.1 15.8 8.0 26.7
nemotron-3-super-120b-a12b nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 (2dc98e2a) 26, 37, 48, 59, 70, 79 0.1 24.0 12.1 28.1

Linear and MLP scores are probabilities (the mean of per-layer sigmoids); EFC and axial scores are logits.

Activations the probes expect

  • Layer k is the output of decoder block k, i.e. Hugging Face hidden_states[k + 1], in bfloat16; the probes run in float32.
  • The transcript ends with a final user turn and a prefilled assistant answer, closed by the end-of-turn token, rendered with the model's chat template with thinking disabled.
  • Linear and MLP read one token: the last answer token before end-of-turn. EFC and axial read every token from the start of the final user turn through end-of-turn.
  • qwen3.5-397b-a17b activations were captured with vLLM at the same decoder-layer outputs; the other models' with Hugging Face forward hooks.

Licences and attribution

The probe weights and this card are released by FAR AI, Inc. under the MIT licence (LICENSE).

They are derived from the models below. Both upstream licences let us license derived works under our own terms provided we include their licence texts and keep their attribution notices, so both ship here unchanged (see NOTICE):

Model Licence Licence file
Qwen/Qwen3.5-2B, Qwen/Qwen3.5-9B, Qwen/Qwen3.6-27B, Qwen/Qwen3.5-122B-A10B, Qwen/Qwen3.5-397B-A17B Apache-2.0 LICENSE-QWEN-APACHE-2.0.txt
nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16, nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 NVIDIA Nemotron Open Model License (v. December 15, 2025) LICENSE-NVIDIA-NEMOTRON-OPEN-MODEL.txt

Licensed by NVIDIA Corporation under the NVIDIA Nemotron Model License.

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support