Instructions to use PAUL1122/jch2 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 PAUL1122/jch2 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 PAUL1122/jch2:Q8_0 # Run inference directly in the terminal: llama cli -hf PAUL1122/jch2:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf PAUL1122/jch2:Q8_0 # Run inference directly in the terminal: llama cli -hf PAUL1122/jch2:Q8_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 PAUL1122/jch2:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf PAUL1122/jch2:Q8_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 PAUL1122/jch2:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf PAUL1122/jch2:Q8_0
Use Docker
docker model run hf.co/PAUL1122/jch2:Q8_0
- LM Studio
- Jan
- Ollama
How to use PAUL1122/jch2 with Ollama:
ollama run hf.co/PAUL1122/jch2:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use PAUL1122/jch2 with Docker Model Runner:
docker model run hf.co/PAUL1122/jch2:Q8_0
- Lemonade
How to use PAUL1122/jch2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull PAUL1122/jch2:Q8_0
Run and chat with the model
lemonade run user.jch2-Q8_0
List all available models
lemonade list
- Atomic Chat
Download unsloth.Q8_0.gguf from PAUL1122/jch2: direct link, hf CLI and curl.
- Browser
- Download file 3.42 GB
-
https://huggingface.co/PAUL1122/jch2/resolve/main/unsloth.Q8_0.gguf
- Command line
-
hf download hf://PAUL1122/jch2/unsloth.Q8_0.gguf
-
curl -L -o unsloth.Q8_0.gguf https://huggingface.co/PAUL1122/jch2/resolve/main/unsloth.Q8_0.gguf
3.42 GB
- Xet hash:
- 529a7892ffed000c025f55e7dd227315b418eedc4fc10a39f1228b6ec1f872a3
- Size of remote file:
- 3.42 GB
- SHA256:
- 6372ead43ba24932e0fa777164843f56f858aa5b2be5e21529d6373dbb75870b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.