autotrust-jev

62 an hour ago

AutoTrust’s decision models return choices, yes/no probabilities, and ratings for the questions you supply

vision decision 9b 35b 
curl http://localhost:11434/v1/systemone \
  -H "Content-Type: application/json" \
  -d '{
    "model": "autotrust-jev",
    "state": "Hello World",
    "questions": {
      "says_hello": {
        "type": "noul",
        "instructions": "Does the state text contain a greeting?",
        "criteria": {
          "true": "The state text contains a greeting.",
          "false": "The state text does not contain a greeting."
        }
      }
    }
  }'

Models

View all →

11 models

autotrust-jev:latest

11GB · 256K context window · Text · an hour ago

autotrust-jev:9b

latest

11GB · 256K context window · Text · an hour ago

autotrust-jev:35b

26GB · 256K context window · Text, Image · an hour ago

Readme

AutoTrust’s decision models return choices, yes/no probabilities, and ratings for the questions you supply. Use them to route requests, classify documents, or grade an answer against your own criteria.

  • Decisions from your criteria: define the categories or six rating levels that matter to your workflow.
  • Probabilities for every option: use the full distribution when deciding what to automate or send for review.
  • Several questions, one input: ask about the same text or structured state in a single request.

Try it

Route a customer request to the right team:

ollama run autotrust-jev "My card was charged twice for the same order. Please refund the duplicate charge." \
  --ask "Which team should handle this request?" \
  --choice "billing=Charges, payments, and refunds" \
  --choice "shipping=Deliveries and tracking" \
  --choice "technical=App errors and account access"

autotrust-jev runs AutoTrust’s 9B text model. For decisions about images, choose autotrust-jev:27b-vl or autotrust-jev:35b.

See the decision documentation for CLI options and the API.

Publisher results

AutoTrust reports these results for its 9B checkpoint on its held-out test_set_30k evaluation:

Task Publisher result
Yes/no AUROC, all evaluation rows 0.996
Rating mean absolute error, 0–5 scale 0.103

See AutoTrust’s evaluation for the target distributions, data sources, and methodology.

Credits

Published by AutoTrust: 9B, 27B-VL, and 35B.

Released under Apache 2.0.