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Error code: JWTInvalidSignature
Exception: InvalidSignatureError
Message: Signature verification failed
Traceback: Traceback (most recent call last):
File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
decoded = jwt.decode(
jwt=token,
...<2 lines>...
options=options,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
decoded = self.decode_complete(
jwt,
...<8 lines>...
leeway=leeway,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
decoded = self._jws.decode_complete(
jwt,
...<3 lines>...
detached_payload=detached_payload,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
self._verify_signature(
~~~~~~~~~~~~~~~~~~~~~~^
signing_input,
^^^^^^^^^^^^^^
...<4 lines>...
options=merged_options,
^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
raise InvalidSignatureError("Signature verification failed")
jwt.exceptions.InvalidSignatureError: Signature verification failedNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Crosscoder Multilayer Split Activations
Raw split activation artifacts for multilayer SPARC-style crosscoder training.
This dataset stores reusable base-only and aligned-only activation tensors. These
are intended to be assembled into matched activations.pt training artifacts
before crosscoder training.
Versions
v1
Source local run: interp_utils/crosscoder/results-multi-v1
Layout:
v1/
base_activations/
smollm3-union/
llama32-3b-union/
qwen3-4b-union/
aligned_activations/
smollm3-{dpo,grpo,kto,orpo,ppo,simpo}/
llama32-3b-{dpo,grpo,kto,orpo,ppo,simpo}/
qwen3-4b-{dpo,grpo,kto,orpo,ppo,simpo}/
Each run directory contains:
run_meta.json
activations/base_activations.pt # base-only runs
activations/aligned_activations.pt # aligned-only runs
The base tensors contain union layer sets. The aligned tensors contain each aligned model's target probe-best layer window. Assembly slices/reorders the base union tensor to the aligned run's layers.
v1 Base Layers
smollm3-union: [16, 17, 18, 19, 20]
llama32-3b-union: [10, 11, 12, 13, 14, 23, 24, 25, 26]
qwen3-4b-union: [19, 20, 21, 22, 23, 24, 25]
Use
Download one base union and one aligned run, then assemble locally with:
.venv/bin/python -m interp_utils.crosscoder.main \
--stage assemble \
--crosscoder-kind multilayer_sparc \
--base-activations-dir path/to/base_union_dir \
--aligned-activations-dir path/to/aligned_run_dir \
--output-dir path/to/assembled_run_dir
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