---

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

for use with llama.cpp,

Ollama, LM Studio, and compatible runtimes.

> Released under Apache-2.0. Built with Qwen — see NOTICE.

Files

| File | Quant | Size (approx) | Use when |

|---|---|---|---|

| marvy-1-14B-Q4_K_M.gguf | Q4_K_M | ~9 GB | Default — best size/quality balance, laptops |

| marvy-1-14B-Q8_0.gguf | Q8_0 | ~16 GB | Highest fidelity, near-FP16 quality |

Quick start

Ollama

ollama run hf.co/MainStack/marvy-1-14B-GGUF:Q4_K_M

llama.cpp

./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/.

1. Load it, set the system prompt below, temperature ~0.4.
2. 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 — see 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.

📖 Full usage (all runtimes + OpenCode wiring): USAGE.md ·

Validate it works: VALIDATION.md

Provenance & limitations

See the merged model card 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 — see 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 §4) and cite the entry on the

merged model card.