---
base_model: Qwen/Qwen3-1.7B
tags:
- llmcompressor
- quantization
- pruning
- SparseGPT_unstruct_0.2_bs128_damp0.01
---
# Compressed Model: MilyaShams/Qwen3-1.7B-SparseGPT_unstruct_0.2_bs128_damp0.01

This model was compressed using the `llmcompressor` framework. 

## Compression Details
- **Base Model:** Qwen/Qwen3-1.7B
- **Experiment Name:** SparseGPT_unstruct_0.2_bs128_damp0.01
- **Recipe / Modifiers Applied:**
```python
index=None group=None start=None end=None update=None initialized_=True finalized_=True started_=True ended_=True sparsity=0.2 sparsity_profile=None mask_structure='0:0' owl_m=None owl_lmbda=None sequential_update=False sequential_targets=['Qwen3DecoderLayer'] targets=['Linear'] ignore=[] block_size=128 dampening_frac=0.01 preserve_sparsity_mask=False offload_hessians=False
```
Note: This model card was automatically generated. All structural modifiers and parameters used during compression are logged above.