Instructions to use tizhong/aplaca_llms 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 tizhong/aplaca_llms 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 tizhong/aplaca_llms:Q4_0 # Run inference directly in the terminal: llama cli -hf tizhong/aplaca_llms:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tizhong/aplaca_llms:Q4_0 # Run inference directly in the terminal: llama cli -hf tizhong/aplaca_llms:Q4_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf tizhong/aplaca_llms:Q4_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf tizhong/aplaca_llms:Q4_0
Use Docker
docker model run hf.co/tizhong/aplaca_llms:Q4_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use tizhong/aplaca_llms with Ollama:
ollama run hf.co/tizhong/aplaca_llms:Q4_0
- Unsloth Desktop
- Docker Model Runner
How to use tizhong/aplaca_llms with Docker Model Runner:
docker model run hf.co/tizhong/aplaca_llms:Q4_0
- Lemonade
How to use tizhong/aplaca_llms with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tizhong/aplaca_llms:Q4_0
Run and chat with the model
lemonade run user.aplaca_llms-Q4_0
List all available models
lemonade list
- Atomic Chat
Download tokenizer.model from tizhong/aplaca_llms: direct link, hf CLI and curl.
- Browser
- Download file 758 kB
-
https://huggingface.co/tizhong/aplaca_llms/resolve/main/tokenizer.model
- Command line
-
hf download hf://tizhong/aplaca_llms/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/tizhong/aplaca_llms/resolve/main/tokenizer.model
758 kB
- Xet hash:
- d345a5fae02c2fa9580ecefc71f99f52a44bfc1e590c3c7aefe43ecaf2e44ec6
- Size of remote file:
- 758 kB
- SHA256:
- 2d967e855b1213a439df6c8ce2791f869c84b4f3b6cfacf22b86440b8192a2f8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.