Instructions to use danielsaggau/lbert_scotus_classsification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsaggau/lbert_scotus_classsification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielsaggau/lbert_scotus_classsification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielsaggau/lbert_scotus_classsification") model = AutoModelForSequenceClassification.from_pretrained("danielsaggau/lbert_scotus_classsification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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 sha256:0b4eea0ad45af2abd3332f74ebe81e466232df0ba595c0e3745f87dea16da8ce
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size 437962832
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