cygnet:12b
2 TagsUpdated 12B params16384 context100+ languagesApache-2.0by blockbrain-ai
Gemma 4 12B IT (Q8_0) with Cygnet's prompt and temperature 3.4: 0.683 on typed decisions, up to 20 options.
multilingual12b
ollaya run cygnet:12b --preset triage "I was charged twice for my subscription this month and want a refund."curl http://localhost:11435/api/decide \
-H "Content-Type: application/json" \
-d '{
"model": "cygnet:12b",
"state": "I was charged twice for my subscription this month and want a refund.",
"questions": {
"department": {
"type": "choice",
"instructions": "Which team should handle this?",
"criteria": {
"billing": "Payments, invoices and refunds",
"technical": "Bugs, errors and outages",
"account": "Login, profile and settings"
}
},
"refund": {
"type": "noul",
"instructions": "Is the customer asking for a refund?"
}
}
}'# Already using a TypeSafe SDK? Set TYPESAFE_BASE_URL=http://localhost:11435 instead.
import requests
response = requests.post(
"http://localhost:11435/api/decide",
json={
"model": "cygnet:12b",
"state": "I was charged twice for my subscription this month and want a refund.",
"questions": {
"department": {
"type": "choice",
"instructions": "Which team should handle this?",
"criteria": {
"billing": "Payments, invoices and refunds",
"technical": "Bugs, errors and outages",
"account": "Login, profile and settings"
}
},
"refund": {
"type": "noul",
"instructions": "Is the customer asking for a refund?"
}
}
},
)
answers = response.json()["answers"]
print(answers["department"]["choice"], answers["refund"]["noul"])const response = await fetch("http://localhost:11435/api/decide", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: "cygnet:12b",
state: "I was charged twice for my subscription this month and want a refund.",
questions: {
department: {
type: "choice",
instructions: "Which team should handle this?",
criteria: {
billing: "Payments, invoices and refunds",
technical: "Bugs, errors and outages",
account: "Login, profile and settings"
}
},
refund: {
type: "noul",
instructions: "Is the customer asking for a refund?"
}
}
}),
});
const { answers } = await response.json();
console.log(answers.department.choice, answers.refund.noul);Details
- weightsabfc3044b937 · 12.7 GB
gguf · Q8_0 · huggingface.co/ggml-org/gemma-4-12B-it-GGUF/resolve/e3e6817…/gemma-4-12B-it-Q8_0.gguf - decision9f8101a4a32d · 2 KB
{"engine": "llama", "family": "cygnet", "layout": "cygnet-v1", "gguf": {…}, …} - calibrationc474a28d0466 · 175 B
{"temperature": [3.4, 3.4, 3.4]} - license0e3d9fc27a00 · 10 KB
Cygnet by blockbrain-ai (https://github.com/blockbrain-ai/cygnet-recipe), a prompt and calibration for Gemma 4 12B IT by Google DeepMind, MIT. The weights are google/gemma-4-12B-it (Apache-2.0), as ggml-org's GGUF conversion of the revision Cygnet pins.
Every layer is checked against its sha256 when it is pulled. Weights and tokenizers download from the model author's Hugging Face repository at a pinned commit; Ollaya never re-hosts them.