Instructions to use mradermacher/Quyen-Plus-v0.1-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Quyen-Plus-v0.1-i1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Quyen-Plus-v0.1-i1-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/Quyen-Plus-v0.1-i1-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 mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Quyen-Plus-v0.1-i1-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 mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Quyen-Plus-v0.1-i1-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 mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Quyen-Plus-v0.1-i1-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 mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/Quyen-Plus-v0.1-i1-GGUF with Ollama:
ollama run hf.co/mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M
- Unsloth Studio
How to use mradermacher/Quyen-Plus-v0.1-i1-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mradermacher/Quyen-Plus-v0.1-i1-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mradermacher/Quyen-Plus-v0.1-i1-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mradermacher/Quyen-Plus-v0.1-i1-GGUF to start chatting
- Docker Model Runner
How to use mradermacher/Quyen-Plus-v0.1-i1-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/Quyen-Plus-v0.1-i1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Quyen-Plus-v0.1-i1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Quyen-Plus-v0.1-i1-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- 7662830dc87507392d9b33cde8bc16560c16612f26c3e237a3290ad7e6471e46
- Size of remote file:
- 4.51 GB
- SHA256:
- 16b9c4e3842524498f2446a75fac48185f92dcc726da6bf42da95590f74c4bc4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.