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QinEmPeRoR93/
nassila-sanad-12b

Name: nassila-sanad-12b
Availability: InStock

google/gemma-4-12B-it

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Nassila Sanad 12B (quality tier)

Checkpoint: S14 (legacy train label v1.14)

Local GGUF for Sanad in Nassila — checks manuscript claims against source excerpts and returns structured JSON with verdicts and verbatim quotes.

File: nassila-sanad-12b-q6_k.gguf · Q6_K · ~9.1 GB
Default tier: nassila-sanad-4b

Part of Nassila Ouroboros — see the 4B model card for the seven-worker overview.

Sanad today: validated on abstract excerpts (Tier 2). Full paper body text is planned (Tier 3).

Combined	Quote validity	False-supported
90.43%	100%	2.86%

Quality-tier validation: PASS

Usage

Quick start (Nassila + LM Studio)

Recommended — download this GGUF, load it in LM Studio, and start the Local Server at http://localhost:1234. ~12 GB+ VRAM recommended.

In Nassila: Settings → Passage grounding → runner LM Studio → model nassila-sanad-12b (or the id LM Studio shows).

Ollama

Requires Ollama 0.5+ and a public Hugging Face repo.

Pull from Hub:

ollama pull huggingface.co/QinEmPeRoR93/nassila-sanad-12b:Q6_K

In Nassila: runner Ollama → base URL http://localhost:11434 → model name from ollama list (often nassila-sanad-12b:Q6_K).

Modelfile fallback (private repo or pull tag not indexed)

FROM https://huggingface.co/QinEmPeRoR93/nassila-sanad-12b/resolve/main/nassila-sanad-12b-q6_k.gguf
PARAMETER num_ctx 4096

ollama create nassila-sanad-12b -f Modelfile

Advanced (llama.cpp / vLLM)

Serve the GGUF with any OpenAI-compatible server (ctx-size 4096; requires a recent llama.cpp build with gemma4_unified support). Point Nassila at your base URL and exposed model id.

bash

llama-server -m nassila-sanad-12b-q6_k.gguf \
  --host 127.0.0.1 --port 1234 --ctx-size 4096 --n-gpu-layers 99

Limitations

Trained on abstract excerpts (Tier 2); full paper body (Tier 3) planned.
Advisory only — use with Nassila deterministic guardrails.
Not bundled in the Nassila installer.

Base model

google/gemma-4-12B-it · Gemma Terms of Use