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SlayThat
/
NikiAI-Survival

Text Generation
GGUF
English
unsloth
survival
llama-3
q4_k_m
Model card Files Files and versions
xet
Community

Instructions to use SlayThat/NikiAI-Survival 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 SlayThat/NikiAI-Survival 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 SlayThat/NikiAI-Survival
    # Run inference directly in the terminal:
    llama cli -hf SlayThat/NikiAI-Survival
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf SlayThat/NikiAI-Survival
    # Run inference directly in the terminal:
    llama cli -hf SlayThat/NikiAI-Survival
    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 SlayThat/NikiAI-Survival
    # Run inference directly in the terminal:
    ./llama-cli -hf SlayThat/NikiAI-Survival
    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 SlayThat/NikiAI-Survival
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf SlayThat/NikiAI-Survival
    Use Docker
    docker model run hf.co/SlayThat/NikiAI-Survival
  • LM Studio
  • Jan
  • vLLM

    How to use SlayThat/NikiAI-Survival with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "SlayThat/NikiAI-Survival"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "SlayThat/NikiAI-Survival",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/SlayThat/NikiAI-Survival
  • Ollama

    How to use SlayThat/NikiAI-Survival with Ollama:

    ollama run hf.co/SlayThat/NikiAI-Survival
  • Unsloth Studio

    How to use SlayThat/NikiAI-Survival 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 SlayThat/NikiAI-Survival 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 SlayThat/NikiAI-Survival to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for SlayThat/NikiAI-Survival to start chatting
  • Docker Model Runner

    How to use SlayThat/NikiAI-Survival with Docker Model Runner:

    docker model run hf.co/SlayThat/NikiAI-Survival
  • Lemonade

    How to use SlayThat/NikiAI-Survival with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull SlayThat/NikiAI-Survival
    Run and chat with the model
    lemonade run user.NikiAI-Survival-{{QUANT_TAG}}
    List all available models
    lemonade list
  • Atomic Chat
NikiAI-Survival
808 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
SlayThat's picture
SlayThat
Update README.md
53290e2 verified 1 day ago
  • .gitattributes
    1.58 kB
    Upload folder using huggingface_hub 1 day ago
  • NikiAI-Survival.gguf
    808 MB
    xet
    Upload folder using huggingface_hub 1 day ago
  • README.md
    1.33 kB
    Update README.md 1 day ago