Instructions to use Arki05/Grok-1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arki05/Grok-1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Arki05/Grok-1-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Arki05/Grok-1-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 Arki05/Grok-1-GGUF:IQ1_M # Run inference directly in the terminal: llama cli -hf Arki05/Grok-1-GGUF:IQ1_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Arki05/Grok-1-GGUF:IQ1_M # Run inference directly in the terminal: llama cli -hf Arki05/Grok-1-GGUF:IQ1_M
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 Arki05/Grok-1-GGUF:IQ1_M # Run inference directly in the terminal: ./llama-cli -hf Arki05/Grok-1-GGUF:IQ1_M
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 Arki05/Grok-1-GGUF:IQ1_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Arki05/Grok-1-GGUF:IQ1_M
Use Docker
docker model run hf.co/Arki05/Grok-1-GGUF:IQ1_M
- LM Studio
- Jan
- Ollama
How to use Arki05/Grok-1-GGUF with Ollama:
ollama run hf.co/Arki05/Grok-1-GGUF:IQ1_M
- Unsloth Desktop
- Docker Model Runner
How to use Arki05/Grok-1-GGUF with Docker Model Runner:
docker model run hf.co/Arki05/Grok-1-GGUF:IQ1_M
- Lemonade
How to use Arki05/Grok-1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Arki05/Grok-1-GGUF:IQ1_M
Run and chat with the model
lemonade run user.Grok-1-GGUF-IQ1_M
List all available models
lemonade list
- Atomic Chat
What kind of hardware environment do you use?
I run grok-1-IQ3_XS-split-00001-of-00009.gguf model on my M3 Max 128g MBP with command line
"./server -m grok-1-IQ3_XS-split-00001-of-00009.gguf --port 8888 --host 0.0.0.0 --ctx-size 1024 --parallel 4 -ngl 999 -n 512"
but give me 0.02 tokens per second
Thanks. The really wired is I compile llama.cpp with metal support and run with -ngl 99, still really slow but RAM just 50% usage.
If I merge those splited files into one gguf format file, can I use ./gguf-split --merge to do it?
Yes gguf-split --merge should merge the files. That won't change anything about your memory issues tho.
Maybe look into mmap and how Memory gets reported (cache vs process memory).