Instructions to use DSAC12DSA21E/MyAwesomeModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DSAC12DSA21E/MyAwesomeModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DSAC12DSA21E/MyAwesomeModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DSAC12DSA21E/MyAwesomeModel") model = AutoModel.from_pretrained("DSAC12DSA21E/MyAwesomeModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel
Evaluation Results
All scores are保留三位小数 (kept to three decimal places):
| Benchmark | Score |
|---|---|
| Math Reasoning | 0.950 |
| Logical Reasoning | 0.930 |
| Common Sense | 0.870 |
| Reading Comprehension | 0.860 |
| Question Answering | 0.910 |
| Text Classification | 0.880 |
| Sentiment Analysis | 0.890 |
| Code Generation | 0.920 |
| Creative Writing | 0.910 |
| Dialogue Generation | 0.900 |
| Summarization | 0.890 |
| Translation | 0.880 |
| Knowledge Retrieval | 0.870 |
| Instruction Following | 0.880 |
| Safety Evaluation | 0.860 |
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