---
base_model: Qwen/Qwen3-1.7B
library_name: transformers
pipeline_tag: text-generation
license: apache-2.0
tags:
- qwen3
- gguf
- llama-cpp
- pruning
- structured-pruning
- q4_k_m
---

# Qwen3-1.7B Depth-Aggressive — Q4_K_M GGUF

A structured depth-pruned and recovery-trained variant of
[`Qwen/Qwen3-1.7B`](https://huggingface.co/Qwen/Qwen3-1.7B), converted to GGUF
and quantized as **Q4_K_M** for llama.cpp-compatible runtimes.

## Model changes

- Transformer layers: **28 → 24**
- Removed source layers: **9, 14, 19, 7**
- Parameters: approximately **1.721B → 1.519B**
- Parameters retained: **88.30%**
- Recovery: **100 chat-recovery optimizer steps**
- Recovery objective: assistant-only cross-entropy plus teacher distillation
- GGUF quantization: **Q4_K_M**

## File

| File | Quantization | Size | SHA-256 |
|---|---:|---:|---|
| `Qwen3-1.7B-Depth-Aggressive-Q4_K_M.gguf` | Q4_K_M | 940.82 MiB | `eb836a316bad3d3672d0e182533f8cb306f5783ae68d9fdb8955c5d2fb1184ae` |

## llama.cpp

```bash
llama-cli -m Qwen3-1.7B-Depth-Aggressive-Q4_K_M.gguf -cnv -ngl 99
```

## Notes

The pruning experiment showed the aggressive depth-pruned 1.7B checkpoint at
24 layers and about 1.519B parameters before GGUF quantization. This repository
contains the quantized GGUF build, not the full-precision Transformers weights.

## License

The base model is distributed under the Apache 2.0 license. Review the original
Qwen model repository for its complete terms and documentation.