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QuantFactory/gemma-2-9B-it-advanced-v2.1-GGUF
gemma-2-9B-it-advanced-v2.1-GGUF is a machine learning model from QuantFactory. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
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.gguf84.7 GB · 100%
From the Hugging Face model README
This is quantized version of jsgreenawalt/gemma-2-9B-it-advanced-v2.1 created using llama.cpp
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.
Quantized GGUFs can be found here: https://huggingface.co/jsgreenawalt/gemma-2-9B-it-advanced-v2.1-GGUF I'll link to other quants as they appear.
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.
This model was merged using the della merge method using google/gemma-2-9b-it as a base.
The following models were included in the merge:
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