Instructions to use GetBeholder/Beholder-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 GetBeholder/Beholder-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 GetBeholder/Beholder-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf GetBeholder/Beholder-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf GetBeholder/Beholder-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf GetBeholder/Beholder-GGUF:Q8_0
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 GetBeholder/Beholder-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf GetBeholder/Beholder-GGUF:Q8_0
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 GetBeholder/Beholder-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf GetBeholder/Beholder-GGUF:Q8_0
Use Docker
docker model run hf.co/GetBeholder/Beholder-GGUF:Q8_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use GetBeholder/Beholder-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GetBeholder/Beholder-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": "GetBeholder/Beholder-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/GetBeholder/Beholder-GGUF:Q8_0
- Ollama
How to use GetBeholder/Beholder-GGUF with Ollama:
ollama run hf.co/GetBeholder/Beholder-GGUF:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use GetBeholder/Beholder-GGUF with Docker Model Runner:
docker model run hf.co/GetBeholder/Beholder-GGUF:Q8_0
- Lemonade
How to use GetBeholder/Beholder-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull GetBeholder/Beholder-GGUF:Q8_0
Run and chat with the model
lemonade run user.Beholder-GGUF-Q8_0
List all available models
lemonade list
- Atomic Chat
Commit History
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gc4b (v11 beta): Q8_0 — worn 0.64/attrib 0.89, D42 clean (Q8 |Δ|<=0.02, removal 38/38)
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v10 (cross-attribution v2): gc3 Q8_0 — species + fresh-NPC persona-sink fixed, gate 0/28, removal 38/38, Q8 drift ~0.00
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v9 (persona-sink fix): gc2 Q8_0 — cross-attribution fix (coat-on-persona), gate 4/10->0/10, removal 38/38, Q8 drift |d|<0.02
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gc1 (grounding-clean): Q8_0 — worn P 0.28->0.34 on gold, drift Q8 |Δ|<=0.01, removal 38/38
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tkaug-xa1: cross-attribution basis (54->85%), Q8_0
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tkaug (v0.6, removal-capable): Q8_0 — worn triad add/complete/REMOVE; removal recall 42/42 precision 59-60/60
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rc-cpc2-pad (0.8B, worn 0.67 @ max-new 2048; padding+bronze recipe) — overwrite 2026-07-05
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v5: MIN short-prompt build (Q8_0) + clean README
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Drop throwaway name
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Stable production name (Beholder-Q8_0.gguf)
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Production framing (drop early-test caveat)
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Add Q8_0 GGUF quant
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Add GGUF (native) model card + PolyForm-NC license
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initial commit
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