Merge AIDC-ai-business/Marcoroni-7B-v3, Q-bert/MetaMath-Cybertron-Starling, mistralai/Mistral-7B-Instruct-v0.2 using slerp merge from https://github.com/cg123/mergekit.

After that we trained DPO with HF data.

config.yaml

slices:
  - sources:
      - model: AIDC-ai-business/Marcoroni-7B-v3
        layer_range: [0, 32]
      - model: Q-bert/MetaMath-Cybertron-Starling
        layer_range: [0, 32]
merge_method: slerp
base_model: AIDC-ai-business/Marcoroni-7B-v3
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 
dtype: float16

You can use alpaca template.

template_format = """{system}
### Instruction:
{prompt}

### Response:
"""

RichardErkhov/viethq188_-_Rabbit-7B-v2-DPO-Chat-4bits

Original model description:

license: apache-2.0

RichardErkhov/
viethq188_-_Rabbit-7B-v2-DPO-Chat-4bits