Instructions to use nikchar/ver_model_bert_3_classes_20k_claims with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikchar/ver_model_bert_3_classes_20k_claims with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikchar/ver_model_bert_3_classes_20k_claims")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikchar/ver_model_bert_3_classes_20k_claims") model = AutoModelForSequenceClassification.from_pretrained("nikchar/ver_model_bert_3_classes_20k_claims") - 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 sha256:8bc20e5a054e7726f533f28b9b0ba7c4f7de50e302fbf5baa805af22225cde92
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size 437961724
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