Feature Extraction
Transformers
Safetensors
pivot
decision-making
classification
scoring
custom_code
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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Q1z/Pivot", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training/data_audit.json from Q1z/Pivot: direct link, hf CLI and curl.
- Browser
- Download file 2.53 kB
-
https://huggingface.co/Q1z/Pivot/resolve/main/training/data_audit.json
- Command line
-
hf download hf://Q1z/Pivot/training/data_audit.json
-
curl -L -o data_audit.json https://huggingface.co/Q1z/Pivot/resolve/main/training/data_audit.json
2.53 kB
| { | |
| "dataset": "Yinhaoc/dsbt-cleared-corpus-v1", | |
| "revision": "0afd5031a19ece346b3287b8804ebb6b7c5a276d", | |
| "code_commit": "abaaae3d08a1636df78bb5ec076c8373380dd88e", | |
| "train_rows": 180023, | |
| "frozen_rows": 161023, | |
| "train_frozen_overlap": { | |
| "a_unique": 161870, | |
| "b_unique": 149029, | |
| "overlap_unique": 149029, | |
| "a_fraction": 0.9206709087539383, | |
| "b_fraction": 1.0 | |
| }, | |
| "optimizer_train_frozen_overlap": { | |
| "a_unique": 129814, | |
| "b_unique": 149029, | |
| "overlap_unique": 119550, | |
| "a_fraction": 0.9209330272543793, | |
| "b_fraction": 0.8021928617920002 | |
| }, | |
| "split_sizes": { | |
| "train": 144017, | |
| "val": 18004, | |
| "holdout": 18002 | |
| }, | |
| "train_families": { | |
| "ai2_arc": 3391, | |
| "banking77": 4176, | |
| "boolq": 10077, | |
| "casehold": 36000, | |
| "commonsense_qa": 7695, | |
| "compliance-checklist": 6208, | |
| "csat-rubric-v1": 3200, | |
| "date-deadline": 5792, | |
| "invoice-match": 8240, | |
| "json-schema-valid": 1056, | |
| "mnli_entail_noul": 12000, | |
| "openbookqa": 4363, | |
| "priority-rubric-v1": 9120, | |
| "qasc": 6507, | |
| "refund-receipt-v1": 5120, | |
| "routing-keywords-v1": 240, | |
| "table-row-compare": 3840, | |
| "ticket-sev-rubric": 16992 | |
| }, | |
| "val_families": { | |
| "ai2_arc": 424, | |
| "banking77": 522, | |
| "boolq": 1260, | |
| "casehold": 4500, | |
| "commonsense_qa": 962, | |
| "compliance-checklist": 776, | |
| "csat-rubric-v1": 400, | |
| "date-deadline": 724, | |
| "invoice-match": 1030, | |
| "json-schema-valid": 132, | |
| "mnli_entail_noul": 1500, | |
| "openbookqa": 546, | |
| "priority-rubric-v1": 1140, | |
| "qasc": 814, | |
| "refund-receipt-v1": 640, | |
| "routing-keywords-v1": 30, | |
| "table-row-compare": 480, | |
| "ticket-sev-rubric": 2124 | |
| }, | |
| "holdout_families": { | |
| "ai2_arc": 424, | |
| "banking77": 522, | |
| "boolq": 1260, | |
| "casehold": 4500, | |
| "commonsense_qa": 962, | |
| "compliance-checklist": 776, | |
| "csat-rubric-v1": 400, | |
| "date-deadline": 724, | |
| "invoice-match": 1030, | |
| "json-schema-valid": 132, | |
| "mnli_entail_noul": 1500, | |
| "openbookqa": 545, | |
| "priority-rubric-v1": 1140, | |
| "qasc": 813, | |
| "refund-receipt-v1": 640, | |
| "routing-keywords-v1": 30, | |
| "table-row-compare": 480, | |
| "ticket-sev-rubric": 2124 | |
| }, | |
| "checkpoint_selection_split": "internal_validation_only", | |
| "internal_holdout_selection_use": false, | |
| "frozen_eval_selection_use": false, | |
| "training_plan": { | |
| "batch_size": 64, | |
| "steps_per_epoch": 2251, | |
| "mandatory_epochs": 6, | |
| "mandatory_optimizer_steps": 13506, | |
| "max_epochs": 8, | |
| "max_optimizer_steps": 18008 | |
| } | |
| } |