Instructions to use Zipeng365/WISP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Zipeng365/WISP with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Zipeng365/WISP", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download models/inventory_summary.json from Zipeng365/WISP: direct link, hf CLI and curl.
- Browser
- Download file 2.16 kB
-
https://huggingface.co/Zipeng365/WISP/resolve/main/models/inventory_summary.json
- Command line
-
hf download hf://Zipeng365/WISP/models/inventory_summary.json
-
curl -L -o inventory_summary.json https://huggingface.co/Zipeng365/WISP/resolve/main/models/inventory_summary.json
2.16 kB
| { | |
| "generated_at_utc": "2026-10-02T11:41:13.762559+00:00", | |
| "slurm_job_id": "55930039", | |
| "expected_cells": 1980, | |
| "status_counts": { | |
| "missing_checkpoint": 1620, | |
| "load_and_smoke_verified": 360 | |
| }, | |
| "physical_source_checkpoints": 360, | |
| "physical_source_bytes": 74911659604, | |
| "logical_model_bytes": 74911659604, | |
| "retained_metadata_metric_discrepancies": 31, | |
| "counts_by_method": { | |
| "wisp_ss": { | |
| "method_name": "WISP-SS", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_rc": { | |
| "method_name": "WISP-RC", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_so": { | |
| "method_name": "WISP-SO", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_cse": { | |
| "method_name": "WISP-CSE", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_gis": { | |
| "method_name": "WISP-GIS", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_cis": { | |
| "method_name": "WISP-CIS", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_ese": { | |
| "method_name": "WISP-ESE", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_select5": { | |
| "method_name": "WISP-Select5", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_select7": { | |
| "method_name": "WISP-Select7", | |
| "expected": 180, | |
| "missing_checkpoint": 180 | |
| }, | |
| "wisp_random": { | |
| "method_name": "WISP-Random", | |
| "expected": 180, | |
| "load_and_smoke_verified": 180 | |
| }, | |
| "wisp_evolution": { | |
| "method_name": "WISP-Evolution", | |
| "expected": 180, | |
| "load_and_smoke_verified": 180 | |
| } | |
| }, | |
| "baselines_included": false, | |
| "retrains_performed": 0, | |
| "models_copied": 360, | |
| "pickle_loads_performed": 360, | |
| "notice": "Checkpoint availability, installed-package synthetic smoke tests, and full frozen-prediction verification are separate evidence levels.", | |
| "model_copy_validation_report": "validation/model_validation.json", | |
| "synthetic_prediction_checks_passed": 360, | |
| "saved_prediction_metric_checks_passed": 360, | |
| "full_frozen_prediction_checks_passed": 6 | |
| } | |