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QuantFactory
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Gemma-Radiation-RP-9B-GGUF

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GGUF
mergekit
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How to use from
llama.cpp
Install (macOS, Linux) 
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
# Run inference directly in the terminal:
llama cli -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
Install from WinGet (Windows) 
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
# Run inference directly in the terminal:
llama cli -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
Use pre-built binary 
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
Build from source code 
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Gemma-Radiation-RP-9B-GGUF:
Use Docker 
docker model run hf.co/QuantFactory/Gemma-Radiation-RP-9B-GGUF:
Quick Links

QuantFactory/Gemma-Radiation-RP-9B-GGUF

This is quantized version of Casual-Autopsy/Gemma-Radiation-RP-9B created using llama.cpp

Original Model Card

ToDo: Fill the card with more info.

merge

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

Merge Details

It's a bit of a test merge to dip my toes into merging Gemma 2. Sadly, however, it seems like 8B is my PC's tolerable limit before performance becomes painstakingly and infuriatingly slow, so after this, I might have to sit out on Gemma 2

Merge Method

This model was merged using the Model Stock merge method using Casual-Autopsy/Gemma-Rad-RP as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: crestf411/gemma2-9B-sunfall-v0.5.2
  - model: crestf411/gemma2-9B-daybreak-v0.5
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.5, 0.13, 0.5, 0.13, 0.3]
  - model: crestf411/gemstone-9b
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.13, 0.5, 0.13, 0.5, 0.13]
merge_method: dare_ties
base_model: crestf411/gemma2-9B-sunfall-v0.5.2
parameters:
  normalize: false
  int8_mask: true
dtype: bfloat16

models:
  - model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
  - model: nldemo/Gemma-9B-Summarizer-QLoRA
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.0625, 0.25, 0.0625, 0.25, 0.0625]
  - model: SillyTilly/google-gemma-2-9b-it+rbojja/gemma2-9b-intent-lora-adapter
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.0625, 0.25, 0.0625, 0.25, 0.0625]
  - model: nbeerbower/gemma2-gutenberg-9B
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.25, 0.0625, 0.25, 0.0625, 0.25]
merge_method: ties
base_model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
parameters:
  normalize: false
  int8_mask: true
dtype: bfloat16

models:
  - model: IlyaGusev/gemma-2-9b-it-abliterated
  - model: TheDrummer/Smegmma-9B-v1
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.5, 0.13, 0.5, 0.13, 0.3]
  - model: TheDrummer/Tiger-Gemma-9B-v1
    parameters:
      density: [0.7, 0.5, 0.3, 0.35, 0.65, 0.35, 0.75, 0.25, 0.75, 0.35, 0.65, 0.35, 0.3, 0.5, 0.7]
      weight: [0.13, 0.5, 0.13, 0.5, 0.13]
merge_method: dare_ties
base_model: IlyaGusev/gemma-2-9b-it-abliterated
parameters:
  normalize: false
  int8_mask: true
dtype: bfloat16

models:
  - model: Casual-Autopsy/Gemma-Rad-RP
  - model: Casual-Autopsy/Gemma-Rad-Uncen
  - model: Casual-Autopsy/Gemma-Rad-IQ
merge_method: model_stock
base_model: Casual-Autopsy/Gemma-Rad-RP
dtype: bfloat16
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Paper for QuantFactory/Gemma-Radiation-RP-9B-GGUF