credence:e4b-calibrated
5 TagsUpdated 7.5B params8192 context100+ languagesApache-2.0by Txoka
Separate zero-synthetic checkpoint with a validation-fitted temperature: stronger public calibration, 72.20 % on typed decisions.
multilingual7.5b
ollaya run credence:e4b-calibrated --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": "credence:e4b-calibrated",
"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": "credence:e4b-calibrated",
"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: "credence:e4b-calibrated",
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
- weights7c557d65b742 · 8.7 GB
gguf · Q8_0 · huggingface.co/Txoka/Credence-v1-Gemma4-E4B/resolve/7d5ffc8…/calibrated/model-Q8_0.gguf - decision82df1e25c766 · 2 KB
{"engine": "llama", "family": "winnow", "layout": "winnow-v1", "gguf": {…}, …} - calibration3769c01c5e88 · 240 B
{"temperature": [1.041, 1.041, 1.041]} - licensea5aa25916b90 · 11 KB
Winnow RLCD decision-model project
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.