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 IQSeC-Lab/BinSIGHT-Dobby:Q8_0
# Run inference directly in the terminal:
llama-cli -hf IQSeC-Lab/BinSIGHT-Dobby:Q8_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf IQSeC-Lab/BinSIGHT-Dobby:Q8_0
# Run inference directly in the terminal:
llama-cli -hf IQSeC-Lab/BinSIGHT-Dobby:Q8_0
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 IQSeC-Lab/BinSIGHT-Dobby:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf IQSeC-Lab/BinSIGHT-Dobby:Q8_0
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 IQSeC-Lab/BinSIGHT-Dobby:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf IQSeC-Lab/BinSIGHT-Dobby:Q8_0
Use Docker
docker model run hf.co/IQSeC-Lab/BinSIGHT-Dobby:Q8_0
Quick Links

unsloth_llama_fine-tuned_model : GGUF

This model was finetuned and converted to GGUF format using Unsloth.

Example usage:

  • For text only LLMs: llama-cli -hf vixxnyx/unsloth_llama_fine-tuned_model --jinja
  • For multimodal models: llama-mtmd-cli -hf vixxnyx/unsloth_llama_fine-tuned_model --jinja

Available Model files:

  • llama-3-8b-Instruct.Q8_0.gguf

Ollama

An Ollama Modelfile is included for easy deployment. This was trained 2x faster with Unsloth

Downloads last month
7
GGUF
Model size
8B params
Architecture
llama
Hardware compatibility
Log In to add your hardware

8-bit

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