Instructions to use asddcsd/MyAwesomeModel-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asddcsd/MyAwesomeModel-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="asddcsd/MyAwesomeModel-best")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("asddcsd/MyAwesomeModel-best") model = AutoModel.from_pretrained("asddcsd/MyAwesomeModel-best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel-Best
Best checkpoint selected from the training run based on the highest eval_accuracy.
Selected Checkpoint
- Checkpoint: step_600
- eval_accuracy: 0.310
Evaluation Results (15 benchmarks)
| Benchmark | Score |
|---|---|
| math_reasoning | 0.310 |
| logical_reasoning | 0.310 |
| common_sense | 0.310 |
| reading_comprehension | 0.310 |
| question_answering | 0.310 |
| text_classification | 0.310 |
| sentiment_analysis | 0.310 |
| code_generation | 0.310 |
| creative_writing | 0.310 |
| dialogue_generation | 0.310 |
| summarization | 0.310 |
| translation | 0.310 |
| knowledge_retrieval | 0.310 |
| instruction_following | 0.310 |
| safety_evaluation | 0.310 |
Overall Score
0.310
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