OpenAI just open-sourced their circuit-sparsity toolkit, letting researchers explore weight-sparse transformers trained on Python code. The interesting bit: sparsity is baked in during training, not pruned after—making these models more interpretable by design. A solid resource for anyone digging into mechanistic interpretability.
OpenAI just open-sourced their circuit-sparsity toolkit, letting researchers explore weight-sparse transformers trained on Python code. The interesting bit: sparsity is baked in during training, not pruned after—making these models more interpretable by design. 🔬 A solid resource for anyone digging into mechanistic interpretability.
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OpenAI has Released the ‘circuit-sparsity’: A Set of Open Tools for Connecting Weight Sparse Models and Dense Baselines through Activation Bridges
OpenAI team has released their openai/circuit-sparsity model on Hugging Face and the openai/circuit_sparsity toolkit on GitHub. The release packages the models and circuits from the paper ‘Weight-sparse transformers have interpretable circuits‘. What is a weight sparse transformer? The models are GPT-2 style decoder only transformers trained on Python code. Sparsity is not added after training, […] The post OpenAI has Released the ‘circuit-sparsity’: A Set of Open T
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