Instructions to use Xananthium/Inference-Model-Archive-2026-10 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 Xananthium/Inference-Model-Archive-2026-10 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 Xananthium/Inference-Model-Archive-2026-10:Q8_0 # Run inference directly in the terminal: llama cli -hf Xananthium/Inference-Model-Archive-2026-10:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Xananthium/Inference-Model-Archive-2026-10:Q8_0 # Run inference directly in the terminal: llama cli -hf Xananthium/Inference-Model-Archive-2026-10: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 Xananthium/Inference-Model-Archive-2026-10:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Xananthium/Inference-Model-Archive-2026-10: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 Xananthium/Inference-Model-Archive-2026-10:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Xananthium/Inference-Model-Archive-2026-10:Q8_0
Use Docker
docker model run hf.co/Xananthium/Inference-Model-Archive-2026-10:Q8_0
- LM Studio
- Jan
- Ollama
How to use Xananthium/Inference-Model-Archive-2026-10 with Ollama:
ollama run hf.co/Xananthium/Inference-Model-Archive-2026-10:Q8_0
- Unsloth Desktop
- Pi
How to use Xananthium/Inference-Model-Archive-2026-10 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Xananthium/Inference-Model-Archive-2026-10:Q8_0
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": "Xananthium/Inference-Model-Archive-2026-10:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Xananthium/Inference-Model-Archive-2026-10 with Docker Model Runner:
docker model run hf.co/Xananthium/Inference-Model-Archive-2026-10:Q8_0
- Lemonade
How to use Xananthium/Inference-Model-Archive-2026-10 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Xananthium/Inference-Model-Archive-2026-10:Q8_0
Run and chat with the model
lemonade run user.Inference-Model-Archive-2026-10-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use Xananthium/Inference-Model-Archive-2026-10 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Xananthium/Inference-Model-Archive-2026-10:Q8_0
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 Xananthium/Inference-Model-Archive-2026-10:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Xananthium/Inference-Model-Archive-2026-10 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Xananthium/Inference-Model-Archive-2026-10:Q8_0
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 "Xananthium/Inference-Model-Archive-2026-10:Q8_0" \ --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"
Inference model archive, October 2026
20/20 complete local checkpoints have public, SHA-256-verified uploads. Dedicated tested model repositories and archived legacy checkpoints are listed below. Three incomplete local downloads were excluded. Unused local weights may be removed after backup verification at the owner's request; public backups remain available.
publication-manifest.json contains sizes, hashes and verified revisions. Each checkpoint carries source credits and available local model cards. Measured reports identify tested variants and their limitations. Archived TensorRT exports, probes and GGUF sources are not asserted compatible with native vLLM 0.31.0. Untested checkpoints have no measured accuracy or performance scores.
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