Instructions to use miikhal/Llama-3.1-8B-python-mqp 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 miikhal/Llama-3.1-8B-python-mqp 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 miikhal/Llama-3.1-8B-python-mqp:BF16 # Run inference directly in the terminal: llama cli -hf miikhal/Llama-3.1-8B-python-mqp:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf miikhal/Llama-3.1-8B-python-mqp:BF16 # Run inference directly in the terminal: llama cli -hf miikhal/Llama-3.1-8B-python-mqp:BF16
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 miikhal/Llama-3.1-8B-python-mqp:BF16 # Run inference directly in the terminal: ./llama-cli -hf miikhal/Llama-3.1-8B-python-mqp:BF16
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 miikhal/Llama-3.1-8B-python-mqp:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf miikhal/Llama-3.1-8B-python-mqp:BF16
Use Docker
docker model run hf.co/miikhal/Llama-3.1-8B-python-mqp:BF16
- LM Studio
- Jan
- Ollama
How to use miikhal/Llama-3.1-8B-python-mqp with Ollama:
ollama run hf.co/miikhal/Llama-3.1-8B-python-mqp:BF16
- Unsloth Studio
How to use miikhal/Llama-3.1-8B-python-mqp with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for miikhal/Llama-3.1-8B-python-mqp to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for miikhal/Llama-3.1-8B-python-mqp to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for miikhal/Llama-3.1-8B-python-mqp to start chatting
- Docker Model Runner
How to use miikhal/Llama-3.1-8B-python-mqp with Docker Model Runner:
docker model run hf.co/miikhal/Llama-3.1-8B-python-mqp:BF16
- Lemonade
How to use miikhal/Llama-3.1-8B-python-mqp with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull miikhal/Llama-3.1-8B-python-mqp:BF16
Run and chat with the model
lemonade run user.Llama-3.1-8B-python-mqp-BF16
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Browse files- config.json +1 -1
- model-00001-of-00004.safetensors +1 -1
- model-00002-of-00004.safetensors +1 -1
- model-00003-of-00004.safetensors +1 -1
- model-00004-of-00004.safetensors +1 -1
- unsloth.BF16.gguf +1 -1
- unsloth.Q8_0.gguf +1 -1
config.json
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"torch_dtype": "bfloat16",
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