Instructions to use kacaforyah/Opti-27B 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 kacaforyah/Opti-27B 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 kacaforyah/Opti-27B:F16 # Run inference directly in the terminal: llama cli -hf kacaforyah/Opti-27B:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kacaforyah/Opti-27B:F16 # Run inference directly in the terminal: llama cli -hf kacaforyah/Opti-27B: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 kacaforyah/Opti-27B:F16 # Run inference directly in the terminal: ./llama-cli -hf kacaforyah/Opti-27B: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 kacaforyah/Opti-27B:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf kacaforyah/Opti-27B:F16
Use Docker
docker model run hf.co/kacaforyah/Opti-27B:F16
- Llama new
- LM Studio
- Jan
- vLLM
How to use kacaforyah/Opti-27B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kacaforyah/Opti-27B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kacaforyah/Opti-27B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/kacaforyah/Opti-27B:F16
- Ollama
How to use kacaforyah/Opti-27B with Ollama:
ollama run hf.co/kacaforyah/Opti-27B:F16
- Unsloth Desktop
- Pi
How to use kacaforyah/Opti-27B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kacaforyah/Opti-27B:F16
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "kacaforyah/Opti-27B:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use kacaforyah/Opti-27B with Docker Model Runner:
docker model run hf.co/kacaforyah/Opti-27B:F16
- Lemonade
How to use kacaforyah/Opti-27B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kacaforyah/Opti-27B:F16
Run and chat with the model
lemonade run user.Opti-27B-F16
List all available models
lemonade list
- Hermes Agent
How to use kacaforyah/Opti-27B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kacaforyah/Opti-27B: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 kacaforyah/Opti-27B:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use kacaforyah/Opti-27B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kacaforyah/Opti-27B:F16
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "kacaforyah/Opti-27B:F16" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Commit History
29 days ago
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Update model card; remove two incomplete eval logs
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Update README.md
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Update README.md
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Update README.md
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Update README.md
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Card: domain table paired directly against the 16-bit model; F16 and KL logs published
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Card: KL divergence to the 16-bit logits, Opti vs Q4_K_M under one base
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Card: MMLU-Pro table now includes the 16-bit original and IQ2_M on the same scorer
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Card: eval/ holds the three held-out texts
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Card: cross-domain perplexity vs Q4_K_M (C4, code, fiction) with per-window logs
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runtime README: AMD HIP build line, independent Strix Halo verification
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Card: lead with the 16-bit comparison; Q4_K_M is the size reference, not the yardstick
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Card: measured speed table (Opti = Q4_K_M decode speed on a 3090)
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Card: Q3_K_M row, exact like-for-like size figures
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Licenses: benchmarking explicitly permitted, patent clause narrowed to litigation; card: like-for-like size note
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Hosted API pricing: Basic / Pro / Business, $2 per million tokens
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Ship the Opti runtime in-repo under runtime/ (patch, build.sh, README, license)
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Runtime is open: link the source-available llama.cpp patch
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Model card rewritten for launch (three-angle draft, merged, leak- and claims-reviewed); license 2(d) generalized
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Public-release model card and Opti Model License; drop the internal file name
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Opti-27B.gguf: the public release file (metadata cleaned)
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Rename the vision projector to Opti-27B-mmproj-f16.gguf (server-side copy)
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README: single model
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add qwen38_27b-Opti-IQ2Mfront+Q4KMtail+corr48-q4_0-nomtp.gguf (stripped tail correctors)
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add qwen38_27b-Opti-IQ2Mfront+Q4KMtail+corr48-q8_0-nomtp.gguf (stripped tail correctors)
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README: stripped v2 files, sizes, MMLU-Pro note
c42f453 -
add Opti v2: 2-bit front + Q4_K_M tail + corrector (6.4832 on the ladder)
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README: v2 (2-bit front + 4-bit tail) row and file
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Update README.md
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add mmproj-qwen38_27b-f16.gguf
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add qwen38_27b-IQ2_M+corr-q8_0-nomtp.gguf
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add LICENSE
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add README.md
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initial commit
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