Instructions to use jethrovic/bend-models 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 jethrovic/bend-models 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 jethrovic/bend-models:Q4_K_M # Run inference directly in the terminal: llama cli -hf jethrovic/bend-models:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jethrovic/bend-models:Q4_K_M # Run inference directly in the terminal: llama cli -hf jethrovic/bend-models: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 jethrovic/bend-models:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf jethrovic/bend-models: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 jethrovic/bend-models:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf jethrovic/bend-models:Q4_K_M
Use Docker
docker model run hf.co/jethrovic/bend-models:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use jethrovic/bend-models with Ollama:
ollama run hf.co/jethrovic/bend-models:Q4_K_M
- Unsloth Desktop
- Pi
How to use jethrovic/bend-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jethrovic/bend-models: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": "jethrovic/bend-models:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use jethrovic/bend-models with Docker Model Runner:
docker model run hf.co/jethrovic/bend-models:Q4_K_M
- Lemonade
How to use jethrovic/bend-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jethrovic/bend-models:Q4_K_M
Run and chat with the model
lemonade run user.bend-models-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use jethrovic/bend-models with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jethrovic/bend-models: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 jethrovic/bend-models:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use jethrovic/bend-models with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jethrovic/bend-models: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 "jethrovic/bend-models: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 models/MANIFEST.json from jethrovic/bend-models: direct link, hf CLI and curl.
- Browser
- Download file 4.52 kB
-
https://huggingface.co/jethrovic/bend-models/resolve/main/models/MANIFEST.json
- Command line
-
hf download hf://jethrovic/bend-models/models/MANIFEST.json
-
curl -L -o MANIFEST.json https://huggingface.co/jethrovic/bend-models/resolve/main/models/MANIFEST.json
4.52 kB
| { | |
| "name": "bend-models/models", | |
| "version": "g30-imatrix-1", | |
| "date": "2026-10-14", | |
| "lane": "gap-chase/G30 (from G17 SHIP-DECISION)", | |
| "license": "apache-2.0 (from GGUF general.license; same as upstream bases)", | |
| "note": "Additive tree. The live phone app still fetches kev-4b-q4km/ (unchanged); nothing here is wired into any app.", | |
| "evidence": { | |
| "decision": "/home/omen/lab/fabric/runs/gap-chase/G17/SHIP-DECISION.md", | |
| "kld_kev": "/home/omen/lab/fabric/runs/gap-chase/G2/receipts/kev4b-rep/RECEIPT.md + /home/omen/lab/fabric/runs/gap-chase/G2/receipts/kev4b/RECEIPT.md", | |
| "kld_27b": "/home/omen/lab/fabric/runs/gap-chase/G17/receipts/27b/raw", | |
| "battery": "/home/omen/lab/fabric/runs/gap-chase/G17/receipts/battery/", | |
| "reverify": "/home/omen/lab/fabric/runs/gap-chase/G30/receipts/" | |
| }, | |
| "files": [ | |
| { | |
| "id": "kev-4b-q4km-imat", | |
| "repo_path": "models/kev-4b-q4km-imat/Kev-4B-Q4_K_M-imat.gguf", | |
| "sha256": "0535181cf3164a7271a7d3d1752a9ceab673c32bb316a081133ec238c186b51c", | |
| "bytes": 2709547712, | |
| "quant": "Q4_K_M + imatrix (kev4b-calib)", | |
| "base": "Kev-4B BF16 (sha c690ee43…) incl. shipped cls.output head", | |
| "replaces": "kev-4b-q4km/Kev-4B-Q4_K_M.gguf (plain, sha 93c66545…) — same tensor types/shapes, +288 B metadata", | |
| "kld_vs_bf16": 0.02894, | |
| "kld_shipped": 0.04573, | |
| "top1": 89.81, | |
| "battery": "38/40 labels vs BF16 (flips only on BF16-margin ≤0.104 items); goldens 8/8 (rot3 = lucky flip on a borderline golden)", | |
| "native_gate": "types identical to shipped Q4_K_M → engine compat unchanged; G17 native smoke queued on GPU locks, not yet receipted", | |
| "status": "ship (llama.cpp path); app NOT repointed", | |
| "url": "https://huggingface.co/jethrovic/bend-models/resolve/main/models/kev-4b-q4km-imat/Kev-4B-Q4_K_M-imat.gguf" | |
| }, | |
| { | |
| "id": "kev-4b-iq4xs-imat", | |
| "repo_path": "models/kev-4b-iq4xs-imat/Kev-4B-IQ4_XS-imat.gguf", | |
| "sha256": "8a45e54a03a689368413de3bb6d33c1129ea416dfa7a8aade64c2f8c2c3b47dc", | |
| "bytes": 2514987712, | |
| "quant": "IQ4_XS + imatrix (kev4b-calib)", | |
| "base": "Kev-4B BF16 (sha c690ee43…) incl. shipped cls.output head", | |
| "replaces": "— (new small tier, −185 MiB vs Q4_K_M)", | |
| "kld_vs_bf16": 0.03593, | |
| "kld_shipped": 0.04573, | |
| "top1": 89.22, | |
| "battery": "40/40 labels vs BF16 (best 4-bit row); goldens 7/8 = same as BF16", | |
| "native_gate": "PENDING — llb native greedy gate (G17 sessionkev) queued on GPU locks; must pass before any native-engine/phone use", | |
| "status": "published for llama.cpp; native path BLOCKED until gate receipt", | |
| "url": "https://huggingface.co/jethrovic/bend-models/resolve/main/models/kev-4b-iq4xs-imat/Kev-4B-IQ4_XS-imat.gguf" | |
| }, | |
| { | |
| "id": "qwen38-27b-q4ks-imat-openjev-wide", | |
| "repo_path": "models/qwen38-27b-q4ks-imat-openjev-wide/Qwen3.8-27B-Q4_K_S-imat-openjev-wide.gguf", | |
| "sha256": "c1e505b2e4266d964cc75e8a801e1c54dfec1bd4205c6ea7072d15c9b907fc0f", | |
| "bytes": 15586316480, | |
| "quant": "Q4_K_S + imatrix (qwen38-27b-calib) + openjev-wide metadata", | |
| "base": "Qwen3.8-27B BF16", | |
| "replaces": "board Qwen3.8-27B-Q4_K_S-openjev-wide (plain, sha 47a0bf5b…) — same type mix", | |
| "kld_vs_q6k": 0.02126, | |
| "kld_shipped_vs_q6k": 0.03652, | |
| "top1": 93.3, | |
| "battery": "40/40 labels vs shipped 27B (capfix llama-server); goldens 6/8 = shipped (Kev goldens, consistency only)", | |
| "native_gate": "n/a — board 27B is served by llama-server (capfix), not llb", | |
| "status": "ship (board, llama-server); promotion into the board store is an owner action", | |
| "url": "https://huggingface.co/jethrovic/bend-models/resolve/main/models/qwen38-27b-q4ks-imat-openjev-wide/Qwen3.8-27B-Q4_K_S-imat-openjev-wide.gguf" | |
| }, | |
| { | |
| "id": "imatrix-kev4b-calib", | |
| "repo_path": "models/imatrix/kev4b-calib.imatrix.gguf", | |
| "sha256": "fe439522f2acc99fd040960f045f9582ccb89fe055d570ca883c61600a2f4737", | |
| "bytes": 3626496, | |
| "quant": "imatrix", | |
| "base": "Kev-4B, G2 calib.txt (lab prose, no TDB)", | |
| "status": "provenance", | |
| "url": "https://huggingface.co/jethrovic/bend-models/resolve/main/models/imatrix/kev4b-calib.imatrix.gguf" | |
| }, | |
| { | |
| "id": "imatrix-qwen38-27b-calib", | |
| "repo_path": "models/imatrix/qwen38-27b-calib.imatrix.gguf", | |
| "sha256": "bd707218d6275dbcb342b23846776b306e535f431cb76f316349fa451138488c", | |
| "bytes": 13642656, | |
| "quant": "imatrix", | |
| "base": "Qwen3.8-27B Q4_K_S, G2 calib.txt 202×512", | |
| "status": "provenance", | |
| "url": "https://huggingface.co/jethrovic/bend-models/resolve/main/models/imatrix/qwen38-27b-calib.imatrix.gguf" | |
| } | |
| ] | |
| } |