Instructions to use EXCO123/admdk9 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 EXCO123/admdk9 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 EXCO123/admdk9:Q4_0 # Run inference directly in the terminal: llama cli -hf EXCO123/admdk9:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf EXCO123/admdk9:Q4_0 # Run inference directly in the terminal: llama cli -hf EXCO123/admdk9:Q4_0
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 EXCO123/admdk9:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf EXCO123/admdk9:Q4_0
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 EXCO123/admdk9:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf EXCO123/admdk9:Q4_0
Use Docker
docker model run hf.co/EXCO123/admdk9:Q4_0
- LM Studio
- Jan
- Ollama
How to use EXCO123/admdk9 with Ollama:
ollama run hf.co/EXCO123/admdk9:Q4_0
- Unsloth Desktop
- Docker Model Runner
How to use EXCO123/admdk9 with Docker Model Runner:
docker model run hf.co/EXCO123/admdk9:Q4_0
- Lemonade
How to use EXCO123/admdk9 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EXCO123/admdk9:Q4_0
Run and chat with the model
lemonade run user.admdk9-Q4_0
List all available models
lemonade list
- Atomic Chat
Download training_args.bin from EXCO123/admdk9: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/EXCO123/admdk9/resolve/main/training_args.bin
- Command line
-
hf download hf://EXCO123/admdk9/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/EXCO123/admdk9/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 92a3298548abd168cb395226b717fee5701d45e768cf003e340da3042b2ec472
- Size of remote file:
- 5.5 kB
- SHA256:
- 3555853d3fee86ee709e63bef4d0498eb30df3f44550caa2be396e1290f6bb94
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.