Instructions to use QWDSA12SA/myawesomemodel-best-checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QWDSA12SA/myawesomemodel-best-checkpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="QWDSA12SA/myawesomemodel-best-checkpoint")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("QWDSA12SA/myawesomemodel-best-checkpoint") model = AutoModel.from_pretrained("QWDSA12SA/myawesomemodel-best-checkpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel (best checkpoint โ step_700)
Selected by highest eval_accuracy across all training steps: step_700 achieves the highest eval_accuracy (0.930) among step_100..step_1000.
Detailed Evaluation Results (15 Benchmarks)
| Benchmark | Score |
|---|---|
| math_reasoning | 0.750 |
| logical_reasoning | 0.890 |
| code_generation | 0.760 |
| question_answering | 0.720 |
| reading_comprehension | 0.790 |
| common_sense | 0.820 |
| text_classification | 0.880 |
| sentiment_analysis | 0.850 |
| dialogue_generation | 0.770 |
| summarization | 0.850 |
| translation | 0.860 |
| knowledge_retrieval | 0.750 |
| creative_writing | 0.700 |
| instruction_following | 0.860 |
| safety_evaluation | 0.830 |
Weighted overall score: 0.805
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