Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Indexnusrefather
/
Erebus-RP-12B-Instruct-2608-v1-GGUF

Text Generation
Transformers
GGUF
English
GGUF
RP
Roleplay
Creative
Writer
gemma3
finetune
ERP
Instruct
v1
Creative writing
experimental
rich worldbuilding
conversational
Model card Files Files and versions
xet
Community

Instructions to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-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 Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-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 Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-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 Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-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 Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
    Use Docker
    docker model run hf.co/Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-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": "Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
  • SGLang

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Ollama

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with Ollama:

    ollama run hf.co/Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
  • Unsloth Desktop
  • Docker Model Runner

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with Docker Model Runner:

    docker model run hf.co/Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
  • Lemonade

    How to use Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull Indexnusrefather/Erebus-RP-12B-Instruct-2608-v1-GGUF:Q4_K_M
    Run and chat with the model
    lemonade run user.Erebus-RP-12B-Instruct-2608-v1-GGUF-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
Erebus-RP-12B-Instruct-2608-v1-GGUF
67.5 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
Indexnusrefather's picture
Indexnusrefather
Update README.md
4039413 verified 18 days ago
  • .gitattributes
    1.99 kB
    Upload 3 files 21 days ago
  • Erebus-RP-12B-Instruct-2608-v1.BF16.gguf
    23.5 GB
    xet
    Upload Erebus-RP-12B-Instruct-2608-v1.BF16.gguf 21 days ago
  • Erebus-RP-12B-Instruct-2608-v1.Q3_K_M.gguf
    6.01 GB
    xet
    Upload 3 files 21 days ago
  • Erebus-RP-12B-Instruct-2608-v1.Q4_K_M.gguf
    7.3 GB
    xet
    Upload 3 files 21 days ago
  • Erebus-RP-12B-Instruct-2608-v1.Q5_K_M.gguf
    8.45 GB
    xet
    Upload 3 files 21 days ago
  • Erebus-RP-12B-Instruct-2608-v1.Q6_K.gguf
    9.66 GB
    xet
    Upload Erebus-RP-12B-Instruct-2608-v1.Q6_K.gguf 21 days ago
  • Erebus-RP-12B-Instruct-2608-v1.Q8_0.gguf
    12.5 GB
    xet
    Upload Erebus-RP-12B-Instruct-2608-v1.Q8_0.gguf 22 days ago
  • README.md
    2.05 kB
    Update README.md 18 days ago