---
base_model:
- playable/Playable1
---
### Quark Quantized Playable1

This is a fine-tuned and quark quantized version of Qwen/Qwen2.5-Coder-7B-Instruct using the 'iat-05-1' adapter.

### Model Details
- Base Model: Qwen/Qwen2.5-Coder-7B-Instruct
- Adapter: iat-05-1
- Quantization: Quark / UINT4 / AWQ / BFLOAT16
- Format: SafeTensors
- Perplexity Score:  10.953088
- Dataset: wikitext-2-raw-v1 

### Quark Info
Quantizing with the quantization configuration:
```bash
Config(
    global_quant_config=QuantizationConfig(
        input_tensors=None,
        output_tensors=None,
        weight=QuantizationSpec(
            dtype=Dtype.uint4,
            observer_cls=<class 'quark.torch.quantization.observer.observer.PerGroupMinMaxObserver'>,
            is_dynamic=False,
            qscheme=QSchemeType.per_group,
            ch_axis=-1,
            group_size=128,
            symmetric=False,
            round_method=RoundType.half_even,
            scale_type=ScaleType.float,
            scale_format=None,
            scale_calculation_mode=None,
            qat_spec=None,
            mx_element_dtype=None,
            zero_point_type=ZeroPointType.int32,
            is_scale_quant=False,
        ),
        bias=None,
        target_device=None,
    ),
    layer_type_quant_config={},
    layer_quant_config={},
    kv_cache_quant_config={},
    kv_cache_group=['*k_proj', '*v_proj'],
    min_kv_scale=0.0,
    softmax_quant_spec=None,
    exclude=['[]'],
    algo_config=[
        AWQConfig(
            name="awq",
            scaling_layers=[{'prev_op': 'input_layernorm', 'layers': ['self_attn.q_proj', 'self_attn.k_proj', 'self_attn.v_proj'], 'inp': 'self_attn.q_proj', 'module2inspect': 'self_attn'}, {'prev_op': 'self_attn.v_proj', 'layers': ['self_attn.o_proj'], 'inp': 'self_attn.o_proj'}, {'prev_op': 'post_attention_layernorm', 'layers': ['mlp.gate_proj', 'mlp.up_proj'], 'inp': 'mlp.gate_proj', 'module2inspect': 'mlp'}, {'prev_op': 'mlp.up_proj', 'layers': ['mlp.down_proj'], 'inp': 'mlp.down_proj'}],
            model_decoder_layers="model.layers",
        ),
    ],
    quant_mode=QuantizationMode.eager_mode,
    log_severity_level=1,
    version="0.10",
)
```