Instructions to use apus-ailab/APUS-OpenJev-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apus-ailab/APUS-OpenJev-v1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("apus-ailab/APUS-OpenJev-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "schema": "openjev-five-system-chart-v1", | |
| "source_summary_sha256": "d0f71b15590e1f56c9a75a847dfd7c402cfaf0ffbd09603953ad726a9aab0305", | |
| "panel_manifest_sha256": "f75623564147490918a5ac98e3b14dbb7664bedb756d36c7f30d202446677318", | |
| "questions": 1000, | |
| "parent_groups": 799, | |
| "quotas": { | |
| "browser": 300, | |
| "hs3": 450, | |
| "boolq": 75, | |
| "mnli": 75, | |
| "score": 100 | |
| }, | |
| "claim_scope": "historical base+adapter checkpoint-5949 evaluation; not current merged release validation; not sealed test; no timing claim", | |
| "metric": "valid and correct / all 1000 questions", | |
| "models": [ | |
| { | |
| "name": "APUS-OpenJev 35B-A3B", | |
| "source_name": "35B-A3B final-5949 / 40L", | |
| "correct": 822, | |
| "total": 1000, | |
| "valid": 1000, | |
| "accuracy": 0.822, | |
| "source_predictions_sha256": "3ec05570b05c96617fcea13f95415ebea5296a28f3e187a04a137a88ff6f05f1" | |
| }, | |
| { | |
| "name": "APUS-OpenJev 9B", | |
| "source_name": "Jet1 9B final-5949 / 32L", | |
| "correct": 811, | |
| "total": 1000, | |
| "valid": 1000, | |
| "accuracy": 0.811, | |
| "source_predictions_sha256": "62804823e9148cb76d0f6ebc98733f69a46ea22a0de368a7c9e03f2dbafbcd65" | |
| }, | |
| { | |
| "name": "APUS-OpenJev 4B", | |
| "source_name": "Jet1 4B final-5949 / 32L", | |
| "correct": 805, | |
| "total": 1000, | |
| "valid": 1000, | |
| "accuracy": 0.805, | |
| "source_predictions_sha256": "8f98034b552bb713513b181b6209c75e52be345e46cee3da3867aa69abf6e3e3" | |
| }, | |
| { | |
| "name": "Jev API", | |
| "source_name": "Official Jev 1.13.0", | |
| "correct": 770, | |
| "total": 1000, | |
| "valid": 972, | |
| "accuracy": 0.77, | |
| "source_predictions_sha256": "d255b7e73357027e612b25bee2863f401867c04cd667ac1947e42c10cc0e66aa" | |
| }, | |
| { | |
| "name": "Laya · typed full input", | |
| "source_name": "Laya Typed-decisions full-input / 1c5edc17", | |
| "correct": 505, | |
| "total": 1000, | |
| "valid": 1000, | |
| "accuracy": 0.505, | |
| "source_predictions_sha256": "da922effc80428e0a8d640bf62238cc6682c9c2ec12824009f4d2e059d703578" | |
| } | |
| ] | |
| } | |