Darkest-Tiger-9B-v1-GGUF
This is a creative, uncensored merge of pre-trained language models created using mergekit.
This model was converted to GGUF format from Fentible/Darkest-Tiger-9B-v1
using llama.cpp via the Fentible's GGUF-repo-suite.
GGUF Repo Suite is based on a refactored fork of ggml.ai's GGUF-my-repo space, updated for offline use with windows and support for lower IQ quants.
imatrix.dat generated using bartowski's calibration_datav3.txt
Refer to the original model card for more details on the model.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: TheDrummer/Tiger-Gemma-9B-v3
merge_method: slerp
dtype: bfloat16
slices:
- sources:
- model: sam-paech/Darkest-muse-v1
layer_range: [0, 42]
- model: TheDrummer/Tiger-Gemma-9B-v3
layer_range: [0, 42]
parameters:
t: 0.5
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Fentible/Darkest-Tiger-9B-v1 --hf-file Darkest-Tiger-9B-v1-IQ4_XS.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Fentible/Darkest-Tiger-9B-v1 --hf-file Darkest-Tiger-9B-v1-IQ4_XS.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1
flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo Fentible/Darkest-Tiger-9B-v1 --hf-file Darkest-Tiger-9B-v1-IQ4_XS.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Fentible/Darkest-Tiger-9B-v1 --hf-file Darkest-Tiger-9B-v1-IQ4_XS.gguf -c 2048
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