Instructions to use Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1 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 Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1 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 Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M # Run inference directly in the terminal: llama cli -hf Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M # Run inference directly in the terminal: llama cli -hf Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1: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 Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1: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 Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M
Use Docker
docker model run hf.co/Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1 with Ollama:
ollama run hf.co/Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1 with Docker Model Runner:
docker model run hf.co/Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M
- Lemonade
How to use Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1:Q4_K_M
Run and chat with the model
lemonade run user.Llama-3-Mourse-8B-Instruct-v0.1-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download unsloth.Q4_K_M.gguf from Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1: direct link, hf CLI and curl.
- Browser
- Download file 4.92 GB
-
https://huggingface.co/Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1/resolve/main/unsloth.Q4_K_M.gguf
- Command line
-
hf download hf://Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1/unsloth.Q4_K_M.gguf
-
curl -L -o unsloth.Q4_K_M.gguf https://huggingface.co/Aktioshi/Llama-3-Mourse-8B-Instruct-v0.1/resolve/main/unsloth.Q4_K_M.gguf
4.92 GB
- Xet hash:
- 745713451bd7e5ff83a07e10a1c55ae961df0812d6f2837a9e5a5bd1a93a0d5d
- Size of remote file:
- 4.92 GB
- SHA256:
- 4c763d0f2f591ca67276dd254ebf68d5ed932011ce1628aff1c93ab7db4efac4
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