NeoChen1024/gemma-2-9B-it-advanced-v2.1-exl2-6.0bpw-h8

Exllamav2 Quant of Gemma Advanced V2.1 (6.0bpw, 8bit head)

This is a merge of the 'smartest' advanced fine-tunes available for Gemma-2-9b-it. It includes WPO, SimPO, and SPPO. The merge was performed via the SOTA 'della' merge method. Merge parameters have been hand-tuned for best results. The Q8_0 quant is highly recommended until better quants come along.

Notes and observations:

• The extreme temperature sensitivity from V1 has been fixed, no longer needs to be run at lower temperatures
• Has a somewhat different writing style than any of the parent models
• Great instruction following
• Tracks plot details well and has good situational understanding
• Seems to have a good understanding of psychology, emotions and creative writing
• More 'sane' than base gemma-it, SPPO, or SimPO - not as prone to 'Cruella De Vil' or 'Evil Sorceress' like SPPO or SimPO, when portraying characters
• Would likely serve as a good base for further merges
• I'm looking for a job, if you're hiring. I'm a skilled Python developer who brings strong devops skills along with an ever-growing knowledge of machine learning pipelines and models. Message me if you want to talk about what I can bring to your team.
• Overall, this feels like a very useful and successful merge.

Quantized GGUFs can be found here:

• My quants, Q8_0 tested - jsgreenawalt/gemma-2-9B-it-advanced-v2.1-GGUF
• iMatrix - mradermacher/gemma-2-9B-it-advanced-v2.1-i1-GGUF
• QuantFactory/gemma-2-9B-it-advanced-v2.1-GGUF
• mradermacher/gemma-2-9B-it-advanced-v2.1-GGUF

Thanks to everyone who was kind enough to provide quants!

I'll link to other quants as they appear.

sample ollama Modelfile

FROM /path/to/file/gemma-2-9B-it-advanced-v2.1-Q8_0.gguf
PARAMETER stop "<start_of_turn>"
PARAMETER stop "<end_of_turn>"
PARAMETER num_ctx 8192
TEMPLATE """<start_of_turn>user
{{ if .System }}{{ .System }} {{ end }}{{ .Prompt }}<end_of_turn>
<start_of_turn>model
{{ .Response }}<end_of_turn>"""

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

Merge Details

Merge Method

This model was merged using the della merge method using google/gemma-2-9b-it as a base.

Models Merged

The following models were included in the merge:

• wzhouad/gemma-2-9b-it-WPO-HB
• princeton-nlp/gemma-2-9b-it-SimPO
• UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: google/gemma-2-9b-it 
  - model: wzhouad/gemma-2-9b-it-WPO-HB
    parameters:
      density: 0.55
      weight: 0.6
  - model: princeton-nlp/gemma-2-9b-it-SimPO 
    parameters:
      density: 0.35
      weight: 0.6
  - model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
    parameters:
      density: 0.25
      weight: 0.4
merge_method: della
base_model: google/gemma-2-9b-it
parameters:
  normalize: true
  int8_mask: true
  lambda: 1.0
  epsilon: 0.1
dtype: float16