IHaveNoClueAndIMustPost/SFR-Iterative-DPO-LLaMA-3-11.5B-R-GGUF

A zero training self-merge test of Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R using settings mentioned on mistral-11b-slimorca
It's....not dumber I guess 🤷‍♀️

Simple PPL comparison
perplexity.exe -[MODEL] -f wiki.test.raw -b 512 -ngl 99
SFR-Iterative-DPO-LLaMA-3-8B-R-F16.gguf - Final estimate: PPL = 7.0279 +/- 0.04493
SFR-Iterative-DPO-LLaMA-3-11.5B-R-Q6_K.gguf - Final estimate: PPL = 7.0500 +/- 0.04516
Meta-Llama-3-8B-Instruct-Q6_K - Final estimate: PPL = 8.4727 +/- 0.06308

Tools used / version
Mergekit: c93c9bb
llama.cpp: b2876

merged

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

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

• Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R

Configuration

The following YAML configuration was used to produce this model:

dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 24]
    model: Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R
- sources:
  - layer_range: [8, 24]
    model: Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R
    parameters:
      scale:
      - filter: o_proj
        value: 0.0
      - filter: down_proj
        value: 0.0
      - value: 1.0
- sources:
  - layer_range: [24, 32]
    model: Salesforce/SFR-Iterative-DPO-LLaMA-3-8B-R