Instructions to use ASD123WE/MyAwesomeModel-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ASD123WE/MyAwesomeModel-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ASD123WE/MyAwesomeModel-TestRepo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ASD123WE/MyAwesomeModel-TestRepo") model = AutoModel.from_pretrained("ASD123WE/MyAwesomeModel-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel-TestRepo
This is a test repository for MyAwesomeModel, containing the best checkpoint from the training run (step_1000).
Evaluation Results
| Benchmark | Score |
|---|---|
| Math Reasoning | 0.600 |
| Logical Reasoning | 0.870 |
| Common Sense | 0.800 |
| Reading Comprehension | 0.760 |
| Question Answering | 0.670 |
| Text Classification | 0.890 |
| Sentiment Analysis | 0.860 |
| Code Generation | 0.700 |
| Creative Writing | 0.680 |
| Dialogue Generation | 0.710 |
| Summarization | 0.830 |
| Translation | 0.870 |
| Knowledge Retrieval | 0.740 |
| Instruction Following | 0.820 |
| Safety Evaluation | 0.790 |
Model Architecture
The model uses a BERT architecture with the following configuration:
- Model type: bert
- Architecture: BertModel
Usage
This is a test repository. For production use, please refer to the official MyAwesomeModel repository.
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