function_vector / metadata.json
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{
"model": "Qwen/Qwen2.5-1.5B-Instruct",
"d_model": 1536,
"num_layers": 28,
"num_heads": 12,
"inject_layer": 9,
"best_lambda": 1.0,
"n_incontext": 4,
"n_target_prompts": 15,
"top_heads": [
{
"layer": 24,
"head": 3,
"aie": 0.004586321767419577
},
{
"layer": 20,
"head": 9,
"aie": 0.0027352971956133842
},
{
"layer": 0,
"head": 6,
"aie": 0.0017912477487698197
},
{
"layer": 17,
"head": 7,
"aie": 0.0017713563283905387
},
{
"layer": 20,
"head": 8,
"aie": 0.0016093882732093334
},
{
"layer": 21,
"head": 3,
"aie": 0.0014112978242337704
},
{
"layer": 18,
"head": 10,
"aie": 0.001295118359848857
},
{
"layer": 17,
"head": 3,
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},
{
"layer": 15,
"head": 1,
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},
{
"layer": 19,
"head": 11,
"aie": 0.0007095862529240549
}
],
"sampling_strategy": "Indices 0-29 used as validation (lambda tuning). Indices 30-44 as target queries. Indices 45+ as in-context pool. N=4 in-context examples per prompt, sampled without replacement."
}