Ma7ee7/Qwen3-1.7B-Depth-Aggressive-Q4_K_M-GGUF overview
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 , co…
Runs locally from ~940.8 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3-1.7B-Depth-Aggressive-Q4_K_M.gguf | GGUF | Q4_K_M | 940.8 MB | Download |
Model Details
| Model ID | Ma7ee7/Qwen3-1.7B-Depth-Aggressive-Q4_K_M-GGUF |
|---|---|
| Author | Ma7ee7 |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | Qwen/Qwen3-1.7B |
| Last modified | 2026-07-16T23:34:18.000Z |
Model README
---
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, 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
llama-cli -m Qwen3-1.7B-Depth-Aggressive-Q4_K_M.gguf -cnv -ngl 99Notes
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.
Run Ma7ee7/Qwen3-1.7B-Depth-Aggressive-Q4_K_M-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models