--- license: apache-2.0 base_model: MainStack/marvy-1-14B base_model_relation: quantized pipeline_tag: text-generation language: - en tags: - servicenow - itsm - csdm - delivery - gguf - llama.cpp - ollama - quantized - qwen2.5 --- # marvy-1-14B-GGUF **GGUF quants of marvy-1-14B, the first open LLM for the full ServiceNow delivery lifecycle. Run it locally and privately on Apple Silicon, LM Studio, or Ollama.** GGUF quantizations of [`MainStack/marvy-1-14B`](https://huggingface.co/MainStack/marvy-1-14B) for use with [llama.cpp](https://github.com/ggerganov/llama.cpp), [Ollama](https://ollama.com), [LM Studio](https://lmstudio.ai), and compatible runtimes. > Released under **Apache-2.0**. Built with Qwen โ€” see `NOTICE`. ## Files | File | Quant | Size (approx) | Use when | |---|---|---|---| | `marvy-1-14B-Q4_K_M.gguf` | Q4_K_M | ~9 GB | Default โ€” best size/quality balance, laptops | | `marvy-1-14B-Q8_0.gguf` | Q8_0 | ~16 GB | Highest fidelity, near-FP16 quality | ## Quick start ### Ollama ```bash ollama run hf.co/MainStack/marvy-1-14B-GGUF:Q4_K_M ``` ### llama.cpp ```bash ./llama-cli -hf MainStack/marvy-1-14B-GGUF:Q4_K_M \ -p "Write a ServiceNow user story with acceptance criteria for P1 SLA escalation." \ --temp 0.4 ``` ### LM Studio 1. In the model browser, search `MainStack/marvy-1-14B-GGUF` and download a quant (`Q4_K_M` recommended), **or** drop the `.gguf` into `~/.lmstudio/models/MainStack/marvy-1-14B-GGUF/`. 2. Load it, set the system prompt below, temperature ~0.4. 3. To use from code/OpenCode, start the local server: ```bash lms server start # OpenAI-compatible on http://localhost:1234/v1 ``` ### Use in OpenCode Point OpenCode at the local LM Studio (or llama.cpp) server as an OpenAI-compatible provider โ€” see **[`USAGE.md`](./USAGE.md)** for the exact `opencode.json` snippet. ### Recommended system prompt ``` You are a senior ServiceNow delivery consultant. You produce precise, implementation-grade artifacts: business analyses, requirements, solution design documents, user stories with acceptance criteria, test cases, and validation reviews. You favor out-of-the-box capabilities, cite concrete tables/plugins/sys_ids when relevant, and write in clear professional English. ``` ๐Ÿ“– **Full usage** (all runtimes + OpenCode wiring): [`USAGE.md`](./USAGE.md) ยท **Validate it works:** [`VALIDATION.md`](./VALIDATION.md) ## Provenance & limitations See the [merged model card](https://huggingface.co/MainStack/marvy-1-14B) for the full training data, anonymization methodology, evaluation (test ppl 13.107 on a project-disjoint split), and limitations. Quantization adds the usual minor quality reduction versus the FP16 model. ## License & attribution Dual-licensed: **weights Apache-2.0**, **MainStack contributions (cards, docs, benchmark) CC-BY-4.0** โ€” see [`LICENSING.md`](./LICENSING.md). **If you use marvy-1-14B as a baseline, fine-tune it, distill from it, or evaluate against it, please credit MainStack** and link to https://huggingface.co/MainStack/marvy-1-14B. Keep the `NOTICE` file intact (required by Apache-2.0 ยง4) and cite the entry on the [merged model card](https://huggingface.co/MainStack/marvy-1-14B#citation).