Qmerft

1
1.5B
—
by
sumink
Language Model
OTHER
1.5B params
New
1 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
4GB+ RAM
Mobile
Laptop
Server
Quick Summary

This is a merge of pre-trained language models created using mergekit.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
2GB+ RAM

Code Examples

Configurationyaml
base_model: Qwen/Qwen2.5-1.5B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.9
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-1.5B
  - layer_range: [0, 28]
    model: sumink/Qwenftmodel
Configurationyaml
base_model: Qwen/Qwen2.5-1.5B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.9
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-1.5B
  - layer_range: [0, 28]
    model: sumink/Qwenftmodel
Configurationyaml
base_model: Qwen/Qwen2.5-1.5B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.9
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-1.5B
  - layer_range: [0, 28]
    model: sumink/Qwenftmodel
Configurationyaml
base_model: Qwen/Qwen2.5-1.5B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.9
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-1.5B
  - layer_range: [0, 28]
    model: sumink/Qwenftmodel
Configurationyaml
base_model: Qwen/Qwen2.5-1.5B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.9
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-1.5B
  - layer_range: [0, 28]
    model: sumink/Qwenftmodel
Configurationyaml
base_model: Qwen/Qwen2.5-1.5B
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.9
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-1.5B
  - layer_range: [0, 28]
    model: sumink/Qwenftmodel

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