Instructions to use OmenWorks/bend-4b 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 OmenWorks/bend-4b 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 OmenWorks/bend-4b:Q4_K_M # Run inference directly in the terminal: llama cli -hf OmenWorks/bend-4b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf OmenWorks/bend-4b:Q4_K_M # Run inference directly in the terminal: llama cli -hf OmenWorks/bend-4b: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 OmenWorks/bend-4b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf OmenWorks/bend-4b: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 OmenWorks/bend-4b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf OmenWorks/bend-4b:Q4_K_M
Use Docker
docker model run hf.co/OmenWorks/bend-4b:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use OmenWorks/bend-4b with Ollama:
ollama run hf.co/OmenWorks/bend-4b:Q4_K_M
- Unsloth Desktop
- Pi
How to use OmenWorks/bend-4b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OmenWorks/bend-4b:Q4_K_M
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": "OmenWorks/bend-4b:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use OmenWorks/bend-4b with Docker Model Runner:
docker model run hf.co/OmenWorks/bend-4b:Q4_K_M
- Lemonade
How to use OmenWorks/bend-4b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OmenWorks/bend-4b:Q4_K_M
Run and chat with the model
lemonade run user.bend-4b-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use OmenWorks/bend-4b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OmenWorks/bend-4b:Q4_K_M
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 OmenWorks/bend-4b:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use OmenWorks/bend-4b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OmenWorks/bend-4b:Q4_K_M
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 "OmenWorks/bend-4b:Q4_K_M" \ --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"
|
Download README.md from OmenWorks/bend-4b: direct link, hf CLI and curl.
- Browser
- Download file 1.54 kB
-
https://huggingface.co/OmenWorks/bend-4b/resolve/main/README.md
- Command line
-
hf download hf://OmenWorks/bend-4b/README.md
-
curl -L -o README.md https://huggingface.co/OmenWorks/bend-4b/resolve/main/README.md
1.54 kB
| license: apache-2.0 | |
| base_model: ggml-org/Kev-4B | |
| tags: [gguf, decision-model, chat, llama.cpp] | |
| # bend-4b — one model, two modes | |
| GGUF quants of **Kev-4B** (Apache-2.0, upstream: [ggml-org/Kev-4B-GGUF](https://huggingface.co/ggml-org/Kev-4B-GGUF)) — the **4B model** of the Bend shelf. | |
| **One model, two modes:** a single loaded copy serves **chat** and **structured decisions**; switching modes **swaps heads on the same model** — never a second model, never a reload. See the head shelf: **[bend-heads](https://huggingface.co/OmenWorks/bend-heads)**. | |
| ## Files & provenance (stated changes) | |
| - `Kev-4B-Q8_0.gguf` — Q8_0, 4.48 GB — **byte-identical mirror** of the upstream file (sha256 `7c2ebed90560522c…`, matches ggml-org/Kev-4B-GGUF). No changes. | |
| - `Kev-4B-Q4_K_M.gguf` — Q4_K_M, 3.03 GB — **byte-identical mirror** of upstream's own Q4_K_M (sha256 `33ae6b18926502b2…`, matches ggml-org/Kev-4B-GGUF). No changes. Its decision head `cls.output` is Q8_0 and its embedding Q4_K: the shape the in-browser (WebGPU) decider reads. | |
| - *Replaced 2026-10-17:* this path previously held our own 2.71 GB requant (sha256 `93c66545eff17854…`), whose `cls.output` had been requantized to Q4_K; the in-browser decider refuses that head, so every decision failed. That file remains in this repo's git history. | |
| ## License | |
| Apache-2.0 — full text in `LICENSE` (this repo). Upstream copyright/license notice retained; upstream name credited above and in the filenames. No endorsement by the upstream authors is implied. | |