Instructions to use afdasfaa/MyAwesomeModel-TestRepository with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afdasfaa/MyAwesomeModel-TestRepository with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="afdasfaa/MyAwesomeModel-TestRepository")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("afdasfaa/MyAwesomeModel-TestRepository") model = AutoModel.from_pretrained("afdasfaa/MyAwesomeModel-TestRepository", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: mit
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library_name: transformers
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---
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# MyAwesomeModel
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## Evaluation Results (step_1000 checkpoint)
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### Per-Benchmark Scores
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| Category | Benchmark | Score |
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|---|---|---|
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| Core Reasoning Tasks | Math Reasoning | 0.550 |
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| | Logical Reasoning | 0.819 |
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| | Common Sense | 0.736 |
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| Language Understanding | Reading Comprehension | 0.700 |
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| | Question Answering | 0.607 |
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| | Text Classification | 0.828 |
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| | Sentiment Analysis | 0.792 |
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| Generation Tasks | Code Generation | 0.650 |
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| | Creative Writing | 0.610 |
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| | Dialogue Generation | 0.644 |
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| | Summarization | 0.767 |
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| Specialized Capabilities | Translation | 0.804 |
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| | Knowledge Retrieval | 0.676 |
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| | Instruction Following | 0.758 |
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| | Safety Evaluation | 0.739 |
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### Overall Score
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The weighted overall score for this checkpoint is **0.712**.
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