# Recipe for rwkv7-goose — the configuration that produced each published bundle.
# Schema and the rules for `status`: ../README.md.
# Run it with:  python3 ../../conversion/zoo_convert.py run <name>

["rwkv7-goose-1.5b"]
script = "export_rwkv7_decode.py"
args = ["int8keepproj"]
card = "README.md"
hf_repo = "mlboydaisuke/RWKV7-Goose-1.5B-CoreAI"
source_hf_id = "RWKV/RWKV7-Goose-World3-1.5B-HF"
bundle = "aimodel/rwkv7_goose_1_5b/rwkv7_goose_1_5b.aimodel"
status = "verified"
overlay = true
aot = "xcrun coreai-build compile <bundle>.aimodel --platform iOS --architecture h18p --preferred-compute gpu --min-deployment-version 27.0"
notes = [
  "The card names the ship recipe explicitly: int8keepproj — FFN and LM head weight-only int8",
  "per-block-32 (the --block 32 default), while the recurrence projections (r/k/v/o_proj) and",
  "the LoRA factors stay fp16 because the WKV7 delta rule is precision-sensitive. ~2 GB, gated",
  "127/127. The upload flattened the bundle name, so the mode is not in it; the card is the record.",
  "h18p/ holds the AOT twin.",
]
