Instructions to use Undi95/Xwin-LM-13B-V0.2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Undi95/Xwin-LM-13B-V0.2-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 Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
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 Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
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 Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
Use Docker
docker model run hf.co/Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
- LM Studio
- Jan
- Ollama
How to use Undi95/Xwin-LM-13B-V0.2-GGUF with Ollama:
ollama run hf.co/Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
- Unsloth Desktop
- Docker Model Runner
How to use Undi95/Xwin-LM-13B-V0.2-GGUF with Docker Model Runner:
docker model run hf.co/Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
- Lemonade
How to use Undi95/Xwin-LM-13B-V0.2-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Undi95/Xwin-LM-13B-V0.2-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.Xwin-LM-13B-V0.2-GGUF-Q4_K_S
List all available models
lemonade list
- Atomic Chat
Can you make a Q4_K_M?
It's the only one that I can handle on my 12gb VRAM card
Q4_K_S can be handled on 12GB VRAM in 4K context.
Proof, using koboldcpp.exe --usecublas normal mmq --gpulayers 43 --contextsize 4096 --threads 4
That's why I choose Q4_K_S over Q4_K_M. But if needed, I will do it, just reply to me.
Edit: I will do it anyway, after thinking haha, sorry I'm a little lazy today.
Working on it.
Well TheBloke is doing it right now!
https://huggingface.co/TheBloke/Xwin-LM-13B-v0.2-GGUF/tree/main
Enjoy!
Yeah I know that Q4_K_S is working but Q4_K_M is also working and it's a better quant that's why I wanted that one
Anyway, thanks for the link I'm gonna check it out, good luck with your constant grind of meming the leaderboard with merges, I'm with you on that one, we need better metrics and to get that we want we need to show how we can easily abuse the old ones :^)
