Instructions to use danielsaggau/scotus_experiments_more_steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsaggau/scotus_experiments_more_steps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielsaggau/scotus_experiments_more_steps")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielsaggau/scotus_experiments_more_steps") model = AutoModelForSequenceClassification.from_pretrained("danielsaggau/scotus_experiments_more_steps") - 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:fbf6eca212602e399c4bd266bcd6a5dab8d2164fd17527841f4d362ca272db09
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size 166575224
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