Instructions to use KnutJaegersberg/claim_extraction_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KnutJaegersberg/claim_extraction_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KnutJaegersberg/claim_extraction_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KnutJaegersberg/claim_extraction_classifier") model = AutoModelForSequenceClassification.from_pretrained("KnutJaegersberg/claim_extraction_classifier") - 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 sha256:73521f0a2737e5401c044726da41bd1f1ac8a3c7cb886100a8180e451fbeb5fb
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size 1740308640
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