How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF:# Run inference directly in the terminal:
llama cli -hf QuantFactory/Gemma-2-Ataraxy-Doppel-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-2-Ataraxy-Doppel-9B-GGUF:# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Gemma-2-Ataraxy-Doppel-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-2-Ataraxy-Doppel-9B-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF:Use Docker
docker model run hf.co/QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF:Quick Links
QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF
This is quantized version of lemon07r/Gemma-2-Ataraxy-Doppel-9B created using llama.cpp
Original Model Card
Gemma-2-Ataraxy-Doppel-9B
One last test model.. that you should ignore again.
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 unsloth/gemma-2-9b-it as a base.
Models Merged
The following models were included in the merge:
- princeton-nlp/gemma-2-9b-it-SimPO
- wzhouad/gemma-2-9b-it-WPO-HB
- nbeerbower/Gemma2-Gutenberg-Doppel-9B
Configuration
The following YAML configuration was used to produce this model:
base_model: unsloth/gemma-2-9b-it
dtype: bfloat16
merge_method: della
parameters:
epsilon: 0.1
int8_mask: 1.0
lambda: 1.0
normalize: 1.0
slices:
- sources:
- layer_range: [0, 42]
model: unsloth/gemma-2-9b-it
- layer_range: [0, 42]
model: wzhouad/gemma-2-9b-it-WPO-HB
parameters:
density: 0.55
weight: 0.6
- layer_range: [0, 42]
model: princeton-nlp/gemma-2-9b-it-SimPO
parameters:
density: 0.35
weight: 0.6
- layer_range: [0, 42]
model: nbeerbower/Gemma2-Gutenberg-Doppel-9B
parameters:
density: 0.25
weight: 0.4
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF:# Run inference directly in the terminal: llama cli -hf QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF: