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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tomh/scotus-bert") model = AutoModelForSequenceClassification.from_pretrained("tomh/scotus-bert") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4e3d236b2b62e4f7a34072f864ac44f94a89359df74570820f8c4e14c78dbe87
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size 433302636
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