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:
# pip install -U transformers accelerate # 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
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -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
- Llama new
- 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
IQ3_S 5/9
Browse files
IQ1_S/grok-1-IQ1_S-00005-of-00009.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:f436d69ad34630e61bae0337998864ec8d9f9b6d265464a0e6dce5d62d2f8268
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size 7244823456
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