Instructions to use SOTAagi2030/MyModel-Complete-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SOTAagi2030/MyModel-Complete-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SOTAagi2030/MyModel-Complete-TestRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SOTAagi2030/MyModel-Complete-TestRepo") model = AutoModel.from_pretrained("SOTAagi2030/MyModel-Complete-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload scores.json with huggingface_hub
Browse files- scores.json +4 -4
scores.json
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{
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"math_reasoning": 0.
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"code_generation": 0.
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"text_classification": 0.828,
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"sentiment_analysis": 0.792,
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"question_answering": 0.607,
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"logical_reasoning": 0.819,
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"common_sense": 0.736,
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"reading_comprehension": 0.
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"dialogue_generation": 0.644,
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"summarization": 0.767,
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"translation": 0.804,
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"knowledge_retrieval": 0.676,
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-
"creative_writing": 0.
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"instruction_following": 0.758,
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"safety_evaluation": 0.739
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}
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{
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+
"math_reasoning": 0.550,
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+
"code_generation": 0.650,
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"text_classification": 0.828,
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"sentiment_analysis": 0.792,
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"question_answering": 0.607,
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"logical_reasoning": 0.819,
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| 8 |
"common_sense": 0.736,
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+
"reading_comprehension": 0.700,
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| 10 |
"dialogue_generation": 0.644,
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| 11 |
"summarization": 0.767,
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"translation": 0.804,
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"knowledge_retrieval": 0.676,
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+
"creative_writing": 0.610,
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"instruction_following": 0.758,
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"safety_evaluation": 0.739
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}
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