Instructions to use stanford-nlpxed/prior_knowledge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stanford-nlpxed/prior_knowledge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stanford-nlpxed/prior_knowledge")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("stanford-nlpxed/prior_knowledge") model = AutoModelForSequenceClassification.from_pretrained("stanford-nlpxed/prior_knowledge", device_map="auto") - 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 sha256:919c7dfcf27c271b1cf552b2e671a2acf6f6147f6430b3a76c3ee9a09897d783
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size 1421507704
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