Instructions to use KalaiselvanD/model_bert_check_11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/model_bert_check_11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/model_bert_check_11")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/model_bert_check_11") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/model_bert_check_11") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebe5ebb856bd2cc17caa591227e7382379c7f6b4d2c23cd744d254041f6f0da5
- Size of remote file:
- 46.7 MB
- SHA256:
- f5e076e6513c0e315452fd53530f1851c31c7bd6fb80fde2ac1847cc97b08fff
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