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Obotu
/
POIEO-GGUF

Text Generation
GGUF
English
Yoruba
llama.cpp
lfm2
unsloth
yoruba
english
creative-writing
local-ai
on-device
lfm2.5
conversational
Model card Files Files and versions
xet
Community

Instructions to use Obotu/POIEO-GGUF 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 Obotu/POIEO-GGUF 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 Obotu/POIEO-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf Obotu/POIEO-GGUF:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf Obotu/POIEO-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf Obotu/POIEO-GGUF: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 Obotu/POIEO-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf Obotu/POIEO-GGUF: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 Obotu/POIEO-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf Obotu/POIEO-GGUF:Q4_K_M
    Use Docker
    docker model run hf.co/Obotu/POIEO-GGUF:Q4_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use Obotu/POIEO-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Obotu/POIEO-GGUF"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Obotu/POIEO-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/Obotu/POIEO-GGUF:Q4_K_M
  • Ollama

    How to use Obotu/POIEO-GGUF with Ollama:

    ollama run hf.co/Obotu/POIEO-GGUF:Q4_K_M
  • Unsloth Desktop
  • Docker Model Runner

    How to use Obotu/POIEO-GGUF with Docker Model Runner:

    docker model run hf.co/Obotu/POIEO-GGUF:Q4_K_M
  • Lemonade

    How to use Obotu/POIEO-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull Obotu/POIEO-GGUF:Q4_K_M
    Run and chat with the model
    lemonade run user.POIEO-GGUF-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
POIEO-GGUF
10 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 17 commits
Obotu's picture
Obotu
Upload POIEO-Q5_0.gguf with huggingface_hub
250cc7a verified 3 days ago
  • .gitattributes
    2.05 kB
    Upload POIEO-Q5_0.gguf with huggingface_hub 3 days ago
  • POIEO-Q4_0.gguf
    1.59 GB
    xet
    Upload POIEO-Q4_0.gguf with huggingface_hub 3 days ago
  • POIEO-Q4_K_M.gguf
    1.67 GB
    xet
    Upload POIEO-Q4_K_M.gguf with huggingface_hub 3 days ago
  • POIEO-Q5_0.gguf
    1.9 GB
    xet
    Upload POIEO-Q5_0.gguf with huggingface_hub 3 days ago
  • POIEO-Q5_K_M.gguf
    1.94 GB
    xet
    Upload POIEO-Q5_K_M.gguf with huggingface_hub 3 days ago
  • POIEO-Q8_0.gguf
    2.87 GB
    xet
    Upload POIEO-Q8_0.gguf with huggingface_hub 3 days ago
  • README.md
    6.38 kB
    Upload model trained with Unsloth 3 days ago
  • chat_template.jinja
    1.19 kB
    Upload tokenizer 3 days ago
  • config.json
    1.73 kB
    Trained with Unsloth - config 3 days ago
  • special_tokens_map.json
    434 Bytes
    Upload model trained with Unsloth 3 days ago
  • tokenizer.json
    17.9 MB
    xet
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  • tokenizer_config.json
    23.4 kB
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