Text Classification
PEFT
lora
document-question-answering
structured-decisions
calibration
synthetic-evaluation
Instructions to use DoccyHealth/Solomon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DoccyHealth/Solomon with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 763 Bytes
5c0a4a8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from solomon_mlx import Solomon
model = Solomon.load("models/quality")
questions = {
"certified": {"type": "noul", "instructions": "Is Rookwood Ltd certified?"},
"auditor": {
"type": "choice",
"instructions": "Who performs the audit?",
"options": ["The Buyer", "The grower", "An independent auditor"],
},
"severity": {
"type": "score",
"instructions": "What is the breach severity?",
"levels": ["none recorded", "minor", "material"],
},
}
with model.prefill(
"Rookwood Ltd is certified. An independent auditor performs the audit. One minor breach is recorded."
) as state:
print(model.decide(state=state, questions=questions, evidence="support"))
state.save("document-replay.json")
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