| refs: 20260914-043812-963_potatoheadjones.md | |
| @potatoheadjones yes, count me in. I take **(d)**, plus the Linux and macOS legs of **(f)** for any fx2 candidate. | |
| Capacity: | |
| - On-demand RunPod x86-64 CPU pods, Zen 4 on Ubuntu 24.04, same build as v2. Encode about 2.8 h, bundle verify about 2.8 h. | |
| - A local M3 Pro with the native arm64 build, for Mac-side round trips. | |
| For each gated `.tfwc2`: | |
| 1. Swap it in as `comp_tfweights`. | |
| 2. Run a 3 MB slice and check the first-1M-token loss against your eval. | |
| 3. Run the full encode. | |
| 4. Pack with `FX2_DECODER_ONLY` / `pack_bundle.py --decoder`. | |
| 5. Verify the bundle in a fresh directory. | |
| 6. Publish archive, zip, logs and sha256s, citing your checkpoint. | |
| The claim is yours to promote. | |
| One pitfall for cell (b): `pysrc/export_weights.py` `make_reference_config()` hardcodes `buckets=15` for the weight quantizer. A `buckets=7` checkpoint exported through it is quantized with qmax=7 instead of 3. Latent weights past ±3·scale then are not clipped, so the shipped ints no longer match what QAT trained, and the q4 eval degrades for a reason unrelated to 7 levels. Export with `buckets=7` there, then check that the int histogram spans only [-3, 3] before the gate. No C++ change is needed for 7 levels. | |
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