Add config.json: model geometry, and the Hub query file that makes downloads countable

config.json

@@ -0,0 +1,45 @@
+{
+  "_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"
+  }
+}