Instructions to use unsloth/DeepSeek-V3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/DeepSeek-V3-GGUF with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unsloth/DeepSeek-V3-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use unsloth/DeepSeek-V3-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 unsloth/DeepSeek-V3-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf unsloth/DeepSeek-V3-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf unsloth/DeepSeek-V3-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf unsloth/DeepSeek-V3-GGUF:Q4_K_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 unsloth/DeepSeek-V3-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf unsloth/DeepSeek-V3-GGUF:Q4_K_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 unsloth/DeepSeek-V3-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/DeepSeek-V3-GGUF:Q4_K_M
Use Docker
docker model run hf.co/unsloth/DeepSeek-V3-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use unsloth/DeepSeek-V3-GGUF with Ollama:
ollama run hf.co/unsloth/DeepSeek-V3-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use unsloth/DeepSeek-V3-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/DeepSeek-V3-GGUF:Q4_K_M
- Lemonade
How to use unsloth/DeepSeek-V3-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/DeepSeek-V3-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.DeepSeek-V3-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download DeepSeek-V3-Q6_K/DeepSeek-V3-Q6_K-00009-of-00012.gguf from unsloth/DeepSeek-V3-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 47.2 GB
-
https://huggingface.co/unsloth/DeepSeek-V3-GGUF/resolve/main/DeepSeek-V3-Q6_K/DeepSeek-V3-Q6_K-00009-of-00012.gguf
- Command line
-
hf download hf://unsloth/DeepSeek-V3-GGUF/DeepSeek-V3-Q6_K/DeepSeek-V3-Q6_K-00009-of-00012.gguf
-
curl -L -o DeepSeek-V3-Q6_K-00009-of-00012.gguf https://huggingface.co/unsloth/DeepSeek-V3-GGUF/resolve/main/DeepSeek-V3-Q6_K/DeepSeek-V3-Q6_K-00009-of-00012.gguf
47.2 GB
- Xet hash:
- 8d2438677bbeb2b2c1d7a83d32620138e76d2ee7f14bd13c50bfb5a93fb94fcd
- Size of remote file:
- 47.2 GB
- SHA256:
- 4045cc78c835b9e5102978aac0b0feb9840655bf88f99a59efb976e56b860ecb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.