Instructions to use wellsssada/MyAwesomeModel-TestRepository with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wellsssada/MyAwesomeModel-TestRepository with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wellsssada/MyAwesomeModel-TestRepository")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("wellsssada/MyAwesomeModel-TestRepository") model = AutoModel.from_pretrained("wellsssada/MyAwesomeModel-TestRepository", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MyAwesomeModel-TestRepository
This repository contains the selected best checkpoint for MyAwesomeModel. The checkpoint was selected from the workspace by scanning all available checkpoints and choosing step_1000, which has the highest evaluation score among the discovered checkpoints.
Selected Checkpoint
- Best checkpoint:
checkpoints/step_1000 - Selection basis: highest eval_accuracy / evaluation score across discovered workspace checkpoints
- Overall weighted evaluation score:
0.710
Detailed Evaluation Results for All 15 Benchmarks
All scores below are formatted to three decimal places for the selected best checkpoint (step_1000).
| Benchmark | Score |
|---|---|
| math_reasoning | 0.550 |
| code_generation | 0.650 |
| text_classification | 0.828 |
| sentiment_analysis | 0.792 |
| question_answering | 0.607 |
| logical_reasoning | 0.819 |
| common_sense | 0.736 |
| reading_comprehension | 0.700 |
| dialogue_generation | 0.644 |
| summarization | 0.767 |
| translation | 0.804 |
| knowledge_retrieval | 0.676 |
| creative_writing | 0.610 |
| instruction_following | 0.758 |
| safety_evaluation | 0.739 |
Benchmark Category View
| Category | Benchmark | Score |
|---|---|---|
| Core Reasoning Tasks | Math Reasoning | 0.550 |
| Core Reasoning Tasks | Logical Reasoning | 0.819 |
| Core Reasoning Tasks | Common Sense | 0.736 |
| Language Understanding | Reading Comprehension | 0.700 |
| Language Understanding | Question Answering | 0.607 |
| Language Understanding | Text Classification | 0.828 |
| Language Understanding | Sentiment Analysis | 0.792 |
| Generation Tasks | Code Generation | 0.650 |
| Generation Tasks | Creative Writing | 0.610 |
| Generation Tasks | Dialogue Generation | 0.644 |
| Generation Tasks | Summarization | 0.767 |
| Specialized Capabilities | Translation | 0.804 |
| Specialized Capabilities | Knowledge Retrieval | 0.676 |
| Specialized Capabilities | Instruction Following | 0.758 |
| Specialized Capabilities | Safety Evaluation | 0.739 |
License
This model repository is provided under the MIT License.
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