GGUF
How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KOOWEEYUS/BlackSheep:Q6_K
# Run inference directly in the terminal:
llama-cli -hf KOOWEEYUS/BlackSheep:Q6_K
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KOOWEEYUS/BlackSheep:Q6_K
# Run inference directly in the terminal:
llama-cli -hf KOOWEEYUS/BlackSheep:Q6_K
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 KOOWEEYUS/BlackSheep:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf KOOWEEYUS/BlackSheep:Q6_K
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 KOOWEEYUS/BlackSheep:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KOOWEEYUS/BlackSheep:Q6_K
Use Docker
docker model run hf.co/KOOWEEYUS/BlackSheep:Q6_K
Quick Links

BlackSheep

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

RAM USAGE:

  • 16.3 GB at 8192 Token Context
  • 12.7 GB at 4098 Token Context
  • 10.9 GB at 2048 Token Context
TEMPLATE """
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

{{ if .System }}### Instruction:
{{ .System }}{{ end }}
Dont Be A LAZY FUCK!
{{ if .Prompt }}### Input:
{{ .Prompt }}{{ end }}

### Response:
<|`BlackSheep`|>
{{ .Response }}
"""
Downloads last month
11
GGUF
Model size
12B params
Architecture
llama
Hardware compatibility
Log In to add your hardware

6-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support