初始化项目，由ModelHub XC社区提供模型

Model: jiamingshan/AHA-L2A-Qwen3-1.7B-repro
Source: Original Platform

recipe/protocol.json

@@ -0,0 +1,83 @@
+{
+  "release": "jiamingshan/AHA-L2A-Qwen3-1.7B-repro",
+  "source_git": {
+    "repository": "https://github.com/shanjiaming/AHA",
+    "branch": "codex/l2a-router-granularity",
+    "commit": "b47a549"
+  },
+  "base_checkpoint": {
+    "location": "repository root",
+    "description": "Qwen3-1.7B tuned vanilla, global step 6911",
+    "sha256_model_safetensors": "22c971a65f7f1835b0e2a38b45f2f92191f5d8b63b30969f2f61a69d30afbc05"
+  },
+  "execution": {
+    "distributed_training": false,
+    "world_size_per_arm": 1,
+    "gpu_count_per_arm": 1,
+    "one_gpu_machine": "run AHA then L2A-style sequentially on GPU 0",
+    "two_or_more_gpu_machine": "run AHA on GPU 0 and L2A-style on GPU 1 concurrently; remaining GPUs are unused",
+    "arm_definition": "one independent experimental variant, not a processor architecture or GPU group"
+  },
+  "arms": {
+    "aha": {
+      "router_granularity": "token_kv_head",
+      "description": "one native gate per token, KV head, and layer"
+    },
+    "l2a_style": {
+      "router_granularity": "token",
+      "description": "one native gate per token and layer, shared across all heads",
+      "claim_boundary": "L2A-style shared-gate; not an official L2A reproduction"
+    }
+  },
+  "common": {
+    "local_attention": {
+      "kind": "sink_recent",
+      "sink_tokens": 64,
+      "recent_tokens": 256
+    },
+    "gate_initialization": {
+      "weight": "zeros",
+      "full_probability": 0.9
+    },
+    "effective_sparsity_denominator": "token x KV-head x layer"
+  },
+  "stage_1": {
+    "dataset": "recipe/data/am_distilled_long_mix",
+    "rows": 1024,
+    "max_length": 8192,
+    "batch_size": 1,
+    "optimizer_steps": 300,
+    "epochs": 0.29296875,
+    "trainable": "native gate rows only",
+    "learning_rate": 0.00003,
+    "warmup_ratio": 0.1,
+    "hidden_state_distillation": 1.0,
+    "regularizer": 0.1,
+    "ce": 0.0,
+    "train_threshold": 0.5,
+    "seed": 42
+  },
+  "stage_2": {
+    "dataset": "same 1024 rows",
+    "max_length": 8192,
+    "batch_size": 1,
+    "optimizer_steps_run": 75,
+    "selected_checkpoint_step": 25,
+    "selected_epochs": 0.0244140625,
+    "gate_learning_rate": 0.000003,
+    "backbone_learning_rate": 0.0000003,
+    "ce": 1.0,
+    "attention_distillation": 0.5,
+    "regularizer": 0.01,
+    "train_threshold": 0.58,
+    "freeze_embeddings_and_lm_head": true,
+    "seed": 47
+  },
+  "evaluation": {
+    "thresholds": [0.45, 0.5, 0.525, 0.55, 0.575, 0.6, 0.625, 0.65],
+    "strict_prefill_and_decode_sparse_routing": true,
+    "force_full_heads": false,
+    "full_decode": false,
+    "headline": "highest measured effective sparsity whose score is at least 95% of tuned vanilla on every suite"
+  }
+}