Aster-G2-9B-v1

merge

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

Merge Details

Merge Method

This model was merged using the SLERP method to create an intermediate model. I used the Model Stock merge method after, using the SLERP model as a base.

The idea was to make a nice and smart base model and add in a few pinches of spice.

For some reason it wouldn't let me use any other merge method- it gave me ModelReference errors about my intermediary model for every method except Model Stock for some reason. I'll see if I can fix it and upload my intended task-arithmetic version as a v2.

This is the only one of my like 700 merges that I think uses something novel/interesting enough in its creation to merit an upload.

Named after the aster, a purple-violet star-shaped perennial flower. It's pretty and has a huge family, much like this model.

Models Merged

The following models were included in the merge:

• anthracite-org/magnum-v3-9b-customgemma2

• nbeerbower/gemma2-gutenberg-9B

• grimjim/Magnolia-v1-Gemma2-8k-9B

• UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3

• BeaverLegacy/Smegmma-Deluxe-9B-v1

• ifable/gemma-2-Ifable-9B

Configuration

The following YAML configuration was used to produce this model:

# THIS YAML CONFIGURATION WAS USED TO CREATE THE INTERMEDIARY MODEL.
# slices:
#   - sources:
#     - model: anthracite-org/magnum-v3-9b-customgemma2
#       layer_range: [0, 42]
#     - model: nbeerbower/gemma2-gutenberg-9B
#       layer_range: [0, 42]
# merge_method: slerp
# base_model: nbeerbower/gemma2-gutenberg-9B
# parameters:
#   t:
#     - filter: self_attn
#       value: [0.2, 0.5, 0.4, 0.7, 1]
#     - filter: mlp
#       value: [1, 0.5, 0.3, 0.4, 0.2]
#     - value: 0.5
# dtype: float16

# THIS YAML CONFIGURATION WAS USED TO CREATE ASTER. The E: model is the intermediate
# model created in the previous config.
models:
  - model: E:/models/mergekit/output/intermediate/
  - model: BeaverLegacy/Smegmma-Deluxe-9B-v1
    parameters:
      weight: 0.3
  - model: ifable/gemma-2-Ifable-9B
    parameters:
      weight: 0.3
  - model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
    parameters:
      weight: 0.15
  - model: grimjim/Magnolia-v1-Gemma2-8k-9B
    parameters:
      weight: 0.25
merge_method: model_stock
base_model: E:/models/mergekit/output/intermediate/
dtype: float16

Alright, now back to smashing models together and seeing what happens...