Instructions to use GainEnergy/OGAI-24B-Q6_K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GainEnergy/OGAI-24B-Q6_K-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GainEnergy/OGAI-24B-Q6_K-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use GainEnergy/OGAI-24B-Q6_K-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf GainEnergy/OGAI-24B-Q6_K-GGUF: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 GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: ./llama-cli -hf GainEnergy/OGAI-24B-Q6_K-GGUF: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 GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K
Use Docker
docker model run hf.co/GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K
- LM Studio
- Jan
- Ollama
How to use GainEnergy/OGAI-24B-Q6_K-GGUF with Ollama:
ollama run hf.co/GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K
- Unsloth Desktop
- Docker Model Runner
How to use GainEnergy/OGAI-24B-Q6_K-GGUF with Docker Model Runner:
docker model run hf.co/GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K
- Lemonade
How to use GainEnergy/OGAI-24B-Q6_K-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull GainEnergy/OGAI-24B-Q6_K-GGUF:Q6_K
Run and chat with the model
lemonade run user.OGAI-24B-Q6_K-GGUF-Q6_K
List all available models
lemonade list
- Atomic Chat
GainEnergy/OGAI-24B-Q6_K-GGUF
This model was converted to GGUF format from GainEnergy/OGAI-24B using llama.cpp. Refer to the original model card for more details.
Use with llama.cpp
Install llama.cpp through Homebrew (macOS/Linux):
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo GainEnergy/OGAI-24B-Q6_K-GGUF --hf-file ogai-24b-q6_k.gguf -p "Explain the principles of reservoir simulation in oil and gas engineering."
Server:
llama-server --hf-repo GainEnergy/OGAI-24B-Q6_K-GGUF --hf-file ogai-24b-q6_k.gguf -c 2048
You can also follow the standard usage steps in the llama.cpp repository.
Manual Installation and Execution
Step 1: Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp
Step 2: Build llama.cpp with LLAMA_CURL=1 and optional GPU flags
cd llama.cpp && LLAMA_CURL=1 make
For Nvidia GPUs on Linux, add LLAMA_CUDA=1.
Step 3: Run inference
./llama-cli --hf-repo GainEnergy/OGAI-24B-Q6_K-GGUF --hf-file ogai-24b-q6_k.gguf -p "Explain the impact of wellbore stability on drilling efficiency."
or
./llama-server --hf-repo GainEnergy/OGAI-24B-Q6_K-GGUF --hf-file ogai-24b-q6_k.gguf -c 2048
This model is optimized for oil and gas engineering applications, featuring domain-specific knowledge in drilling, completions, reservoir management, and production optimization.
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