metadata
base_model:
- ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1
- NeverSleep/Lumimaid-v0.2-12B
- nbeerbower/Lyra-Gutenberg-mistral-nemo-12B
- v000000/NM-12B-Lyris-dev-3
- elinas/Chronos-Gold-12B-1.0
library_name: transformers
tags:
- mergekit
- merge
Siskin 0.2
The 0.1 version's writing is more "human" — check it out here
Overview
Somewhat experimental merge of some Nemo models. Consists mostly of human data, so there should be very little gptisms/claudisms. Models work with about ~28k context and could maybe be stretched further.
Note: Both v0.1 and v0.2 can write in the first person despite the initial message. Specify the narrative style somewhere in the prompt to fix this if you don't like it.
Prompt template: Mistral
<s>[INST] {input} [/INST] {output}</s>
Quants
Merge Details
Merge Method
This model was merged using the della_linear merge method using ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1 as a base.
Models Merged
The following models were included in the merge:
- NeverSleep/Lumimaid-v0.2-12B
- nbeerbower/Lyra-Gutenberg-mistral-nemo-12B
- v000000/NM-12B-Lyris-dev-3
- elinas/Chronos-Gold-12B-1.0
Configuration
The following YAML configuration was used to produce this model:
models:
- model: ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1
parameters:
weight: [0.2, 0.3, 0.2, 0.3, 0.2]
density: [0.45, 0.55, 0.45, 0.55, 0.45]
- model: NeverSleep/Lumimaid-v0.2-12B
parameters:
weight: [0.165, 0.295, 0.295, 0.165, 0.165, 0.295, 0.295, 0.165]
density: [0.5]
- model: elinas/Chronos-Gold-12B-1.0
parameters:
weight: [0.01768, -0.01675, 0.01285, -0.01696, 0.01421]
density: [0.6, 0.4, 0.5, 0.4, 0.6]
- model: v000000/NM-12B-Lyris-dev-3
parameters:
weight: [0.208, 0.139, 0.139, 0.139, 0.208]
density: [0.7]
- model: nbeerbower/Lyra-Gutenberg-mistral-nemo-12B
parameters:
weight: [0.33]
density: [0.45, 0.55, 0.45, 0.55, 0.45]
merge_method: della_linear
base_model: ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1
parameters:
epsilon: 0.04
lambda: 1.05
int8_mask: true
rescale: true
normalize: false
dtype: bfloat16
tokenizer_source: base