Marco-01-slerp6-7B

1
7.0B
license:apache-2.0
by
allknowingroger
Language Model
OTHER
7B params
New
0 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
16GB+ 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
7GB+ RAM

Code Examples

Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
Configurationyaml
models:
  - model: AIDC-AI/Marco-o1
  - model: allknowingroger/Qwen2.5-7B-task2
merge_method: slerp
base_model: AIDC-AI/Marco-o1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers

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