cflow / config.json
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Add config.json: model geometry, and the Hub query file that makes downloads countable
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{
"_comment": "Geometry of model.cflow, read from its own .cflow v5 header. cflow is a standalone Rust runtime, not a transformers architecture: `model_type` and `architectures` are deliberately absent so nothing tries to load this with transformers. See README.md for how to run it.",
"library_name": "cflow",
"model_name": "arch2_4_8k_16l",
"cflow_format_version": 5,
"num_hidden_layers": 16,
"hidden_size": 8192,
"vocab_size": 50257,
"tokenizer": "gpt2",
"num_attention_heads": 128,
"num_key_value_heads": 128,
"head_dim": 64,
"attention": "uniform",
"sliding_window": null,
"rope_theta": 10000.0,
"rms_norm_eps": 1e-06,
"intermediate_size": 32768,
"hidden_act": "gelu_pytorch_tanh",
"num_experts": 8,
"num_experts_per_tok": 2,
"moe_intermediate_size": 4096,
"combine_style": "DelayedSum",
"dense_delay": 1,
"expert_delay": 2,
"quantization": {
"method": "cflow-q4_0",
"bits": 4,
"group_size": 32,
"tile_rows": 128,
"tile_cols": 256
},
"_notes": {
"params": "~31B total, ~1.9B per layer",
"rms_norm_eps": "not recorded in the v5 header; the runtime substitutes 1e-6, which is the value this model was trained with",
"rope_theta": "not recorded in the v5 header; the runtime defaults to 10000, which is this model's base",
"delays": "dense_delay=1 and expert_delay=2 are the pipeline-native schedule; they change the dependency graph, not just the order of execution"
}
}