Instructions to use apasi/BertClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apasi/BertClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="apasi/BertClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("apasi/BertClassifier") model = AutoModelForSequenceClassification.from_pretrained("apasi/BertClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efd567af5681529b753aaf03cf3f84e72072566485e6b7dd9f31aa711b23912c
- Size of remote file:
- 3.96 kB
- SHA256:
- 1cac5060e01f14538bbcbf02e65dc0da72ab15ab21cccc5f81baafb88c602825
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