Instructions to use danielsaggau/scotus_CLS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsaggau/scotus_CLS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielsaggau/scotus_CLS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielsaggau/scotus_CLS") model = AutoModelForSequenceClassification.from_pretrained("danielsaggau/scotus_CLS") - 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 sha256:84c90745f10d2e1c641a425e238d6b72caf979ac67ca4541aa7bf42f8733e4d7
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size 166575224
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