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README.md
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- **Creators**: Intel Labs
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- **Version**:
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- **License**: [Intel Research and Development License](.\Intel_OBL_Internal_RD_Use_License.md)
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- **Number of Training Samples**:
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- **Number of Test Samples**:
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- **Format**:
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## Intended Use
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- **Primary Uses**:
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## Data Collection Process
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## Ethical Considerations
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- **Creators**: Intel Labs
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- **Version**: 1.0 (Updated: 2025-05-02)
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- **License**: [Intel Research and Development License](.\Intel_OBL_Internal_RD_Use_License.md)
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- **Number of Training Samples**: >100M
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- **Number of Test Samples**: >500K
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- **Format**: pyarrow format
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## Intended Use
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- **Primary Uses**:
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- These intermediate features or tokens are primarily intended for insights and exploratory analysis in explainable AI, as well as for training ad-hoc models such as linear probes, Sparse AutoEncoders (SAEs), or transcoders.
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- This is also an example of a dataset that can be extracted using the feature recorder (intercept_manager) from the BlueGlass repository, providing a guiding dataset for further analysis.
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- **Out-of-Scope Uses**: This dataset is not intended for commercial use or for training models that will be deployed in real-world scenarios without further verification and validation.
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## Data Collection Process
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This dataset contains intermediate features extracted from various layers of transformer models using the intercept_manager module from [BlueGlass](https://github.com/IntelLabs/blueglass). The features are recorded from different probe positions within the model, as illustrated in the image below, enabling fine-grained analysis and interoperability.
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<div align="center">
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<img src="docs/images/feature_pattern.png" alt="Feature Pattern used to extract the BlueLens dataset" width="300"/>
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</div>
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## Ethical Considerations
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<!-- DON'T CHANGE THIS SECTION -->
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