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README.md

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+---
+base_model:
+- wzhouad/gemma-2-9b-it-WPO-HB
+- UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
+- princeton-nlp/gemma-2-9b-it-SimPO
+library_name: transformers
+tags:
+- mergekit
+- merge
+- merge
+---
+# Gemma Advanced V2.1
+
+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](https://huggingface.co/jsgreenawalt/gemma-2-9B-it-advanced-v2.1-GGUF)
+* [iMatrix  -  mradermacher/gemma-2-9B-it-advanced-v2.1-i1-GGUF](https://huggingface.co/mradermacher/gemma-2-9B-it-advanced-v2.1-i1-GGUF)
+* [QuantFactory/gemma-2-9B-it-advanced-v2.1-GGUF](https://huggingface.co/QuantFactory/gemma-2-9B-it-advanced-v2.1-GGUF)
+* [mradermacher/gemma-2-9B-it-advanced-v2.1-GGUF](https://huggingface.co/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
+```yaml
+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](https://github.com/cg123/mergekit).
+
+## Merge Details
+### Merge Method
+
+This model was merged using the della merge method using [google/gemma-2-9b-it](https://huggingface.co/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](https://huggingface.co/wzhouad/gemma-2-9b-it-WPO-HB)
+* [princeton-nlp/gemma-2-9b-it-SimPO](https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO)
+* [UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+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
+
+```