HMS-Slerp-12B-v2

2
12.0B
2 languages
—
by
yamatazen
Language Model
OTHER
12B params
New
0 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
27GB+ 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
12GB+ RAM

Code Examples

Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union
Configurationyaml
base_model: yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
models:
  - model: yamatazen/Himeyuri-Magnum-12B
merge_method: slerp
dtype: bfloat16
parameters:
  normalize: true
  t: [0.25, 0.3, 0.5, 0.3, 0.25]
tokenizer:
  source: union

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