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EREN121232
/
MAJESTIC-FIN-R1-gguf

Text Generation
Safetensors
GGUF
English
lfm2
llama.cpp
ollama
unsloth
conversational
Model card Files Files and versions
xet
Community

Instructions to use EREN121232/MAJESTIC-FIN-R1-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • llama-cpp-python

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="EREN121232/MAJESTIC-FIN-R1-gguf",
    	filename="MAJESTIC-FIN-R1-F16.gguf",
    )
    
    llm.create_chat_completion(
    	messages = [
    		{
    			"role": "user",
    			"content": "What is the capital of France?"
    		}
    	]
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    # Run inference directly in the terminal:
    llama-cli -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    # Run inference directly in the terminal:
    llama-cli -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    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 EREN121232/MAJESTIC-FIN-R1-gguf:F16
    # Run inference directly in the terminal:
    ./llama-cli -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    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 EREN121232/MAJESTIC-FIN-R1-gguf:F16
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    Use Docker
    docker model run hf.co/EREN121232/MAJESTIC-FIN-R1-gguf:F16
  • LM Studio
  • Jan
  • vLLM

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "EREN121232/MAJESTIC-FIN-R1-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": "EREN121232/MAJESTIC-FIN-R1-gguf",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/EREN121232/MAJESTIC-FIN-R1-gguf:F16
  • Ollama

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with Ollama:

    ollama run hf.co/EREN121232/MAJESTIC-FIN-R1-gguf:F16
  • Unsloth Studio new

    How to use EREN121232/MAJESTIC-FIN-R1-gguf 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 EREN121232/MAJESTIC-FIN-R1-gguf 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 EREN121232/MAJESTIC-FIN-R1-gguf to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for EREN121232/MAJESTIC-FIN-R1-gguf to start chatting
  • Pi new

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "EREN121232/MAJESTIC-FIN-R1-gguf:F16"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf EREN121232/MAJESTIC-FIN-R1-gguf:F16
    Configure Hermes
    # Install Hermes:
    curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
    hermes setup
    # Point Hermes at the local server:
    hermes config set model.provider custom
    hermes config set model.base_url http://127.0.0.1:8080/v1
    hermes config set model.default EREN121232/MAJESTIC-FIN-R1-gguf:F16
    Run Hermes
    hermes
  • Docker Model Runner

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with Docker Model Runner:

    docker model run hf.co/EREN121232/MAJESTIC-FIN-R1-gguf:F16
  • Lemonade

    How to use EREN121232/MAJESTIC-FIN-R1-gguf with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull EREN121232/MAJESTIC-FIN-R1-gguf:F16
    Run and chat with the model
    lemonade run user.MAJESTIC-FIN-R1-gguf-F16
    List all available models
    lemonade list
MAJESTIC-FIN-R1-gguf
18.2 GB
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  • 1 contributor
History: 9 commits
EREN121232's picture
EREN121232
Add local Ollama Modelfile
60f7dc1 verified 23 days ago
  • .gitattributes
    1.64 kB
    Add Q8_0 GGUF export 23 days ago
  • MAJESTIC-FIN-R1-F16.gguf
    5.14 GB
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  • MAJESTIC-FIN-R1-Q8_0.gguf
    2.73 GB
    xet
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  • Modelfile
    344 Bytes
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  • README.md
    1.31 kB
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  • chat_template.jinja
    1.3 kB
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  • config.json
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  • gitattributes
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  • model (1).safetensors
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  • model.safetensors
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  • params
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  • template
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  • tokenizer.json
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  • tokenizer_config.json
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