Instructions to use microsoft/SportsBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/SportsBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/SportsBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("microsoft/SportsBERT") model = AutoModelForMaskedLM.from_pretrained("microsoft/SportsBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Parent(s): bf6af8b
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README.md
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@@ -5,3 +5,6 @@ SportsBERT is a BERT model trained from scratch with specific focus on sports ar
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"Anthony Davis is a [MASK]" would give out the tokens "legend", "superstar", "rookie", "star", "king" in descending confidences.
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This model can then be used to fine tune for other tasks such as classification, entity extraction, etc.
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"Anthony Davis is a [MASK]" would give out the tokens "legend", "superstar", "rookie", "star", "king" in descending confidences.
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This model can then be used to fine tune for other tasks such as classification, entity extraction, etc.
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Language: English
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pipeline_tag: fill-mask
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