Instructions to use tomh/scotus-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomh/scotus-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tomh/scotus-bert", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tomh/scotus-bert") model = AutoModelForSequenceClassification.from_pretrained("tomh/scotus-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6e1d760d9e8461661a276e02c107a1fc5ef19939be26bc540dae517dee452c8
- Size of remote file:
- 433 MB
- SHA256:
- 668d5fc5de84928ad56a4f1f458ad0396bd2943b4c688ed8f741c65c44b49902
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