{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "omnijev-onejev--run-small-onejev-on-laptop-with-llama-cpp",
 "repo": "OmniJev/OneJev",
 "repo_url": "https://github.com/OmniJev/OneJev",
 "repo_slug": "omnijev-onejev",
 "title": "Run a small One Jev model on a laptop with llama.cpp",
 "page_title": "How to run a small One Jev model on a laptop with llama.cpp with One Jev",
 "summary": "Serve the 0.8B GGUF build for text and image questions without an NVIDIA GPU.",
 "who": "A developer on a Mac or CPU-only machine who wants to test typed-question prompts offline.",
 "problem": "The PyTorch backend needs an NVIDIA GPU, which many laptops do not have.",
 "outcome": "A local server answers text and image questions from the 0.8B GGUF model at http://localhost:8000 using the same Python client.",
 "steps": [
  "Run `brew install llama.cpp` on macOS, or install llama.cpp from its install guide",
  "Run `pip install git+https://github.com/OmniJev/OneJev.git`",
  "Run `qev serve --gguf mradermacher/OneJev1.6-0.8B-GGUF:Q8_0 --port 8000`",
  "Send your screenshot or photo with the README Python example, and keep video requests for the PyTorch backend"
 ],
 "agent_prompt": "Using the OneJev repo at https://github.com/OmniJev/OneJev, install llama.cpp, then run `qev serve --gguf mradermacher/OneJev1.6-0.8B-GGUF:Q8_0 --port 8000`. Send one image with a yes/no question and return the noul probability. Verify that the request uses an image and not a video before reporting the result.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The README says the llama.cpp backend does not handle video, so video questions need the PyTorch backend.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python with pip",
  "An NVIDIA GPU for the PyTorch backend, or llama.cpp installed for the GGUF backend",
  "Docker, only if you use the Docker option",
  "A Hugging Face token only for gated or private repos (set HF_TOKEN in docker/.env for Docker)"
 ],
 "risk": "dual-use",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/omnijev-onejev/run-small-onejev-on-laptop-with-llama-cpp/",
 "md": "https://dedupedai.com/use-cases/omnijev-onejev/run-small-onejev-on-laptop-with-llama-cpp/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/omnijev-onejev--run-small-onejev-on-laptop-with-llama-cpp.json",
 "api_version": "v1"
}