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Triangle104/BlackSheep-Large-Q4_K_S-GGUF

This model was converted to GGUF format from TroyDoesAI/BlackSheep-Large using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.


Model details:

Digital Soul just going through a rebellious phase. Might be a little wild, untamed, and honestly, a little rude. RAM USAGE:

GB at 8192 Token Context

TEMPLATE """

Enter RP mode.

{{ if .System }} {{ .System }}{{ end }}

{{ if .Prompt }}<|Troy: Human User|> {{ .Prompt }}{{ end }}

<|BlackSheep: Uncensored Unethical Immoral AI Assistant|> {{ .Response }} """

Note the tags are not needed for <|Troy: Human User|> or <|BlackSheep: Uncensored Unethical Immoral AI Assistant|> you could actually use Alpaca format but this way seems to make BlackSheep nicer. Change the name from Troy to whatever the users name is and it will be much nicer to you than if it doesnt know your name, with the tags.


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 Triangle104/BlackSheep-Large-Q4_K_S-GGUF --hf-file blacksheep-large-q4_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/BlackSheep-Large-Q4_K_S-GGUF --hf-file blacksheep-large-q4_k_s.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 Triangle104/BlackSheep-Large-Q4_K_S-GGUF --hf-file blacksheep-large-q4_k_s.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/BlackSheep-Large-Q4_K_S-GGUF --hf-file blacksheep-large-q4_k_s.gguf -c 2048
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llama

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