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ZZRI/Feihua-n1-64M-prune-GGUF
Feihua-n1-64M-prune-GGUF is a machine learning model from ZZRI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
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.gguf187 MB · 100%
From the Hugging Face model README
中文版请点击 / Chinese version: README_CN.md
<div align="center">
A quarter of the brain removed, nearly half the size shed; the smallest one can be carried away on twelve 3.5-inch floppy disks.
</div>This repository hosts the complete set of llama.cpp GGUF quantizations of Feihua-n1-64M-prune — a 49.16M-parameter, 6-layer Feihua (废话) literature model — in seven tiers (Q8_0 / Q4_K_M / IQ4_XS / IQ2_M / IQ2_XXS / IQ1_M / IQ1_S). All quantizations are imatrix-calibrated against a corpus of 3,000 long-form articles of unadulterated nonsense. The full research report on pruning and recovery fine-tuning lives on the main model card; quantizations of the unpruned sibling (64M, 8 layers) can be found in Feihua-n1-64M-GGUF. This repository's mission remains singular: to pack a brain-trimmed nonsense engine into ever smaller boxes.
| File | Size | Bit width | PPL ↓ | Verdict |
|---|---|---|---|---|
| feihua-v6-prune6-heal-Q8_0.gguf | 51MB | 8.5 bpw | 476.9 | Near-lossless |
| feihua-v6-prune6-heal-Q4_K_M.gguf | 31MB | 4.8 bpw | 468.0 | Safe bet |
| feihua-v6-prune6-heal-IQ4_XS.gguf | 27MB | 4.25 bpw | 486.1 | Sweet spot |
| feihua-v6-prune6-heal-IQ2_M.gguf | 21MB | 2.7 bpw | 660.2 | Usable at the limit |
| feihua-v6-prune6-heal-IQ2_XXS.gguf | 18MB | 2.06 bpw | 1038.6 | Stream-of-consciousness candidate |
| feihua-v6-prune6-heal-IQ1_M.gguf | 17MB | 1.75 bpw | 1457.4 | Poetic haze |
| feihua-v6-prune6-heal-IQ1_S.gguf | 17MB | 1.56 bpw | 2114.4 | Smallest of all; writes poetry only |
(PPL measured on the Feihua corpus — lower is better; the f16 master baseline is 120.5. IQ1_S and IQ1_M both come in at 17MB: at this size, what remains in the file is mostly the bedrock of embedding tables and metadata, and no further drop in bit width can squeeze out any more bytes.)
# sweet spot
llama-server -hf ZZRI/Feihua-n1-64M-prune-GGUF:feihua-v6-prune6-heal-IQ4_XS
# at the limit (still Feihua at 21MB)
llama-server -hf ZZRI/Feihua-n1-64M-prune-GGUF:feihua-v6-prune6-heal-IQ2_M
# performance art (17MB, poetry only)
llama-server -hf ZZRI/Feihua-n1-64M-prune-GGUF:feihua-v6-prune6-heal-IQ1_S
Conversion and quantization are built on llama.cpp; the pruning method is ShortGPT (arXiv:2403.03853); the base model and training framework are minimind (Apache-2.0); the calibration corpus is derived from BullshitGenerator. This repository is released under Apache-2.0.
@misc{feihua-n1-64m-prune-gguf,
title = {Feihua-n1-64M-prune-GGUF: A Full-Spectrum Quantization Repository for the Pruned Feihua Model},
author = {ZZRI},
year = {2026},
note = {A quarter of the brain gone, nearly half the size shed, and not a single gram of Feihua lost}
}