Team Ai
Modelpublic

guidelabs/steerling-8b

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face
118likes156downloads
Model Card

Steerling-8B:

An interpretable causal diffusion language model with concept steering.

Paper: Scaling Inherently Interpretable Language Models Code: github.com/guidelabs/steerling Project page: guidelabs.ai/papers/scaling-inherently-interpretable-language-models

Steerling-8B is an 8 billion parameter language model that combines masked diffusion with interpretable concept decomposition. Unlike standard autoregressive LLMs, Steerling generates text by iteratively unmasking tokens in order of confidence, and decomposes its internal representations into human-interpretable concepts that can be inspected and steered.

Quick Start

bash
pip install steerling
python
from steerling import SteerlingGenerator, GenerationConfig

generator = SteerlingGenerator.from_pretrained("guidelabs/steerling-8b")

text = generator.generate(
    "The key to understanding neural networks is",
    GenerationConfig(max_new_tokens=100, seed=42),
)
print(text)

Model Details

PropertyValue
Parameters8.4B
ArchitectureCausalDiffusionLM + iGuide
Context Length4,096
Vocabulary100,281 (cl100k_base + specials)
Known Concepts33,732
Unknown Concepts101,196
GQA32 heads, 4 KV heads
Diff Block Size64
Precisionbfloat16
VRAM Required~18GB

Architecture

Steerling uses block-causal attention, bidirectional within a block, and causal across blocks. The interpretable concept heads decompose transformer hidden states into:

hidden → known_features + unknown_features + epsilon = composed → logits
  • —known_features: Weighted sum of top-k learned concept embeddings (interpretable and maps to understandable features)
  • —unknown_features: Residual captured by a factorized unknown head (101,196 concepts, rank 256)
  • —epsilon: Small correction for reconstruction fidelity

Training Data

DatasetLicenseStage
Nemotron-CC-HQ (real + synthetic)NVIDIA Data AgreementPretraining
Dolmino Mix (math)ODC-By v1.0Midtraining

The Nemotron-CC dataset includes synthetic data generated by third-party models (Qwen, DeepSeek). Users should review the applicable license terms for their intended use case.

GPU Requirements

SetupWorks?
A100 80GB✅
A100 40GB✅
A6000 48GB✅
RTX 4090 24GB✅
RTX 3090 24GB✅
16GB or less❌

License

The Steerling source code and model weights are released under the Apache License 2.0.

The model weights are provided for research and evaluation purposes. The weights were trained on datasets with varying license terms, including Nemotron-CC-HQ and Dolmino Mix. Some training data includes synthetic content generated by third-party models with their own license terms. We are currently reviewing the implications of these upstream licenses for downstream use of the model weights. Please check back for updates on the weight licensing terms.

For questions about commercial use of the model weights, contact us at info@guidelabs.ai