---
license: apache-2.0
base_model: ATH-MaaS/Marco-Nano-Instruct
library_name: transformers
pipeline_tag: text-generation
tags:
- reap
- pruning
- qwen3_moe
- moe
- safetensors
---

# Marco-Nano-Instruct REAP Pruned 0.25

This is a pruned derivative of `ATH-MaaS/Marco-Nano-Instruct`, produced with
`CerebrasResearch/reap` layerwise REAP pruning in a Codex-assisted experiment
(GPT5.5 xhigh based).

## Details

- Pruning method: REAP layerwise pruning
- Requested compression ratio: `0.25`
- Experts retained: `174`
- Experts per token: `8`
- Calibration dataset: `theblackcat102/evol-codealpaca-v1`
- `model_max_length`: `2048`
- `batches_per_category`: `128`
- `batch_size`: `1`
- `batch_group_size`: `8`
- Format: safetensors

## Notes

This checkpoint was created for a low-resource pruning experiment on a 6GB VRAM
environment. Benchmark evaluation was not run. A short prompt smoke check showed
usable English output, but Japanese and Chinese outputs may still show
repetition, self-continuation, or wording artifacts.