Feature Extraction
Transformers
Safetensors
English
pivot
custom_code
decision-making
classification
routing
scoring
Instructions to use Q1z/Pivot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Q1z/Pivot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Q1z/Pivot", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Q1z/Pivot", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,784 Bytes
2d8be88 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | {
"model": "Pivot",
"contract": "unstructured_state_in__typed_probabilistic_decisions_out",
"state": "Customer dispute: invoice 120 vs PO 100, age=3d, region=US",
"decisions": [
{
"id": "route",
"primitive": "choice",
"description": null,
"options": [
"billing",
"tech",
"sales"
],
"index": 0,
"value": "billing",
"probs": {
"billing": 0.709779679775238,
"tech": 0.013995149172842503,
"sales": 0.27622511982917786
},
"prob_vector": [
0.709779679775238,
0.013995149172842503,
0.27622511982917786
],
"confidence": 0.709779679775238
},
{
"id": "approve",
"primitive": "noul",
"description": null,
"options": [
"true",
"false"
],
"index": 1,
"value": "false",
"probs": {
"true": 0.44199028611183167,
"false": 0.5580097436904907
},
"prob_vector": [
0.44199028611183167,
0.5580097436904907
],
"confidence": 0.5580097436904907,
"p_true": 0.44199028611183167
},
{
"id": "severity",
"primitive": "score",
"description": null,
"options": [
"0",
"1",
"2",
"3"
],
"index": 3,
"value": "3",
"probs": {
"0": 0.007189917378127575,
"1": 0.22580669820308685,
"2": 0.04488111659884453,
"3": 0.7221222519874573
},
"prob_vector": [
0.007189917378127575,
0.22580669820308685,
0.04488111659884453,
0.7221222519874573
],
"confidence": 0.7221222519874573,
"expected": 2.4819356873631477
}
],
"schema_version": "pivot-alpha-v1"
} |