Hi — first of all, wonderful project. 🐦
I ran the full pipeline on my machine and published the result, so others can skip the 756 GB FP8 download and the conversion:
https://huggingface.co/jlnsrk/GLM-5.2-colibri-int4
- Produced with the unmodified converter:
coli convert (--ebits 4 --io-bits 8), including the MTP head — 141 shards + 3 MTP shards + config/tokenizer files, 378.8 GB total, file sizes verified against my local copy.
- Model card explains it's colibrì's own container (not GGUF/AWQ) and links back to this repo. MIT, matching the base weights.
Notes from the run, in case they're useful datapoints:
- Hardware: WSL2 (Ubuntu 24.04) on Windows 11, 24 cores, 24 GB RAM, model dir on the WSL ext4 VHDX.
- Download + conversion of all 141 shards took ~7 h end-to-end (~3.7 min per shard cycle at ~25 MB/s network), fully unattended with
supervisor.sh (adapted paths). The resume logic survived a mid-run reboot flawlessly.
setup.sh built clean with gcc 13, no warnings that stopped anything.
Feel free to link the mirror in the README if you find it useful — and thanks for building this!
Hi — first of all, wonderful project. 🐦
I ran the full pipeline on my machine and published the result, so others can skip the 756 GB FP8 download and the conversion:
https://huggingface.co/jlnsrk/GLM-5.2-colibri-int4
coli convert(--ebits 4 --io-bits 8), including the MTP head — 141 shards + 3 MTP shards + config/tokenizer files, 378.8 GB total, file sizes verified against my local copy.Notes from the run, in case they're useful datapoints:
supervisor.sh(adapted paths). The resume logic survived a mid-run reboot flawlessly.setup.shbuilt clean with gcc 13, no warnings that stopped anything.Feel free to link the mirror in the README if you find it useful — and thanks for building this!