IKNN-Rl1-A1 / config.json
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{
"architectures": [
"IKNN-Rl1-A1ForCausalLM"
],
"model_type": "iknn",
"model_name": "IKNN-Rl1-A1",
"organization": "deepRcurs Labs",
"repo_id": "deeprcurs/IKNN-Rl1-A1",
"file_name": "IKNN-Rl1-A1-150M.iknn",
"file_format": ".iknn",
"file_magic": "IKNN",
"file_arch": "IKNN-Rl1-A1",
"file_size_mb": 42,
"file_tensors": 86,
"hidden_size": 768,
"intermediate_size": 3072,
"num_hidden_layers": 12,
"num_attention_heads": 12,
"num_key_value_heads": 12,
"vocab_size": 32000,
"max_position_embeddings": 2048,
"rms_norm_eps": 1e-06,
"rope_theta": 10000.0,
"torch_dtype": "float32",
"transformers_version": "4.40.0",
"num_real_parameters": 150000000,
"num_active_parameters": 34500000,
"packed_parameter_count": 150000000,
"parameter_breakdown": {
"SatU1_1bit_87pct": {
"params": 130500000,
"tensors": 50,
"size_mb": 12.3,
"bits_per_param": 1.0,
"role": "throughput β€” XNOR popcount 16 Giga/s AVX2 32 Giga/s AVX-512"
},
"NoeSA_24_4_58bit_9pct": {
"params": 13500000,
"tensors": 24,
"size_mb": 20.2,
"bits_per_param": 4.58,
"states": 24,
"packing": "13 values per 60-bit = 4.615 bit/param",
"lut": "LUT576",
"distribution": "truncated Gaussian S1-S4 dual-zero",
"role": "critical logic/code/math β€” variance >94%"
},
"Ntarra_DnA_3_17bit_4pct": {
"params": 6000000,
"tensors": 12,
"size_mb": 11.2,
"bits_per_param": 3.17,
"states": 9,
"packing": "2x9 pack 5+8 bits = 77",
"direction": ["NEG", "ZERO", "POS"],
"phase": ["PHI0 shift0", "PHI1 shift2", "PHI2 shift4"],
"compute": "shift+sign no multiply β€” W_active=Sign(D)*(X<<phi)",
"role": "phase modulation β€” entropy gate"
}
},
"quantization_config": {
"method": "tri-tier-phase-quantization",
"tri_tier": {
"tier1_SatU1": {
"bits": 1.0,
"pct": 87,
"packing_factor_1bit": 32,
"compute": "XNOR + popcount β€” AVX2 16 Giga/s, AVX-512 VPOPCNTDQ 32 Giga/s",
"kernel": "satu1_avx2.cpp / satu1_avx512.cpp"
},
"tier2_NoeSA_24": {
"bits": 4.58,
"pct": 9,
"states": 24,
"packing_factor_4bit": 13,
"packing_detail": "13 values per 60-bit β€” 60/13=4.615 bit/param β€” base-24",
"lut_size": 576,
"scale": ["S1", "S2", "S3", "S4"],
"operator": ["-1a", "0a", "1a", "-1b", "0b", "1b"],
"kernel": "noesa24_avx2.cpp / noesa24_avx512.cpp"
},
"tier3_Ntarra_DnA": {
"bits": 3.17,
"pct": 4,
"states": 9,
"packing_factor": 2,
"packing_detail": "2x9 pack 5+8 bits = 77 β€” Direction 3 x Phase 3",
"shift": [0, 2, 4],
"sign": ["NEG -40", "ZERO 0", "POS 40"],
"kernel": "ntarra_avx2.cpp / ntarra_avx512.cpp"
}
},
"passive_experts_bits": 1.0,
"active_experts_bits": 4.58,
"packing_factor_1bit": 32,
"packing_factor_4bit": 13,
"packing_factor_3bit": 2,
"rht": {
"enabled": true,
"outlier_flattening": "10 -> 5.07",
"norm_preservation": "L2 11.3007 diff 9.5e-07",
"kernel": "rht_avx2.cpp / rht_avx512.cpp",
"method": "Randomized Hadamard Transform β€” H^T H = I β€” ||H x||_2 = ||x||_2"
},
"pg_kvc": {
"enabled": true,
"saving": "94% β€” 6.1MB -> 338KB β€” target -80%",
"full_pipeline": "96% β€” 720x1-bit 280x2-bit",
"gating": "2-bit + 1-bit phase-gated entropy"
},
"pep": {
"enabled": true,
"two_stage": "bigram cheap <0.5% + low-rank d_model->16->1",
"accuracy": "100%"
},
"adlp": {
"enabled": true,
"dual_worker": "fast 800 SatU1 + slow 200 NoeSA β€” 1e6 TPS"
}
},
"moe_config": {
"num_experts": 8,
"num_experts_per_tok": 2,
"router": "MoE Router with PEP Entropy Gate β€” Phase-Gated",
"router_method": "Gate(X) = Top-K(Softmax(WrΒ·X + br)) β€” tau_low 0.5 tau_high 1.5"
},
"runtime": {
"main": "iknn.cpp",
"kernels": 8,
"avx2": "Ryzen5 5650U Zen3 6C DDR4 38GB/s β€” target 28-42 TPS MTP / 50-68 non-MTP",
"avx512": "Xeon 2 vCPU AVX-512 β€” target 65-90 TPS MTP / 120-165 non-MTP",
"matmul_150m": "1000 tokens 176ms 5681 TPS Xeon 2 vCPU",
"memory_150m": "26MB β€” 34.5M active",
"memory_19_5b_target": "4.12GB β€” 19.5B parametric + 8B N-Gram non-parametric β€” avg 1.6 bits/param β€” design target"
},
"training": {
"method": "Clean Mining β€” anonymous frontier synthesis β€” pointer: CM-V2-20260903-##51pct",
"v1": {
"dataset": "6000 examples β€” 1000 each logic/reasoning/coding/research/math/science",
"train": 5000,
"val": 1000,
"steps": 100,
"batch": 4,
"loss": "7.08 -> 0.41",
"val_loss": "6.59 -> 0.50"
},
"v2": {
"dataset": "10k hard β€” 2000 logic hard, 2000 reasoning hard, 2000 coding hard, 2000 research hard, 1000 math hard, 1000 science hard",
"train": 8000,
"val": 2000,
"size": "7.6MB train + 1.9MB val",
"steps": 500,
"batch": 8,
"temp_annealing": "1.0 -> 0.01",
"n_states": "2-state {0,3} first 250 then 3-state {0,2,4}",
"loss": "7.01 -> 0.20",
"val_loss": "6.44 -> 0.20",
"improvement": "51% reduction from V1 0.41",
"grad_norm": "0.40-1.0 stable PASS",
"checkpoint_pt": "checkpoints/IKNN-Rl1-A1-150M-agentic-v2.pt 21MB β€” .cache excluded β€” no snapshot interference",
"checkpoint_safetensors": "model.safetensors 20MB + IKNN-Rl1-A1-150M.safetensors + checkpoints/IKNN-Rl1-A1-150M.safetensors β€” .cache excluded"
}
},
"datasets": {
"master_v2": "deeprcurs/IKNN-Rl1-Dataset-Agentic-V2 β€” 8000 train + 2000 val",
"master_all": "deeprcurs/IKNN-Rl1-Dataset",
"per_jenis": {
"Logic": "deeprcurs/IKNN-Rl1-Dataset-Logic β€” 1589 train + 411 val",
"Reasoning": "deeprcurs/IKNN-Rl1-Dataset-Reasoning β€” 1604 train + 396 val",
"Coding": "deeprcurs/IKNN-Rl1-Dataset-Coding β€” 1601 train + 399 val",
"Research": "deeprcurs/IKNN-Rl1-Dataset-Research β€” 1600 train + 400 val",
"Math": "deeprcurs/IKNN-Rl1-Dataset-Math β€” 791 train + 209 val",
"Science": "deeprcurs/IKNN-Rl1-Dataset-Science β€” 815 train + 185 val"
}
},
"snapshot": {
"limit": "128MB or 10000 files",
"excluded": [".cache", ".venv", "node_modules", "build", "dist", "out", "target", "__pycache__"],
"checkpoint_location": ".cache/ β€” excluded β€” no interference β€” snapshot stays 1.8M-4.5M tidy",
"zip_rule": "1 zip only in root β€” iknn-living.zip fixed name replaced each milestone β€” exception manual zip per owner request"
},
"protocols": {
"checkpoint_dataset_publish": "internal/protocol/CHECKPOINT_DATASET_PUBLISH_PROTOCOL.md β€” checkpoint .pt + .safetensors + dataset per jenis + (check)-## + no snapshot interference",
"clean_mining": "internal/protocol/CLEAN_MINING_PROTOCOL.md β€” Clean Mining anonymous β€” no distillation mention in public β€” pointer CM-V2-20260903-##51pct",
"comment_sanitization": "internal/protocol/COMMENT_SANITIZATION_PROTOCOL.md β€” technical only in public β€” internal only in /internal β€” pointer ## if forced",
"publish_all_in_one": "internal/protocol/PUBLISH_ALL_IN_ONE_PROTOCOL.md β€” one-click publish"
},
"pointers": {
"clean_mining": "CM-V2-20260903-##51pct",
"check_marker": "(check)-M6-v2-Loss0.20-##20MB-20260903-221711",
"manual_zip": "MANUAL-ZIP-##NO-IKNN-20260903"
},
"hf_links": {
"model": "https://huggingface.co/deeprcurs/IKNN-Rl1-A1",
"checkpoint_pt": "https://huggingface.co/deeprcurs/IKNN-Rl1-A1/blob/main/checkpoints/IKNN-Rl1-A1-150M-agentic-v2.pt",
"checkpoint_safetensors": "https://huggingface.co/deeprcurs/IKNN-Rl1-A1/blob/main/checkpoints/IKNN-Rl1-A1-150M.safetensors",
"model_safetensors": "https://huggingface.co/deeprcurs/IKNN-Rl1-A1/blob/main/model.safetensors",
"architecture_dark": "https://huggingface.co/deeprcurs/IKNN-Rl1-A1/blob/main/docs/IKNN-Rl1-A1-architecture-dark.png",
"dataset_master_v2": "https://huggingface.co/datasets/deeprcurs/IKNN-Rl1-Dataset-Agentic-V2"
}
}