Instructions to use KingTechnician/bert-base-uncased_LOGIC_Native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KingTechnician/bert-base-uncased_LOGIC_Native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KingTechnician/bert-base-uncased_LOGIC_Native")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KingTechnician/bert-base-uncased_LOGIC_Native") model = AutoModelForSequenceClassification.from_pretrained("KingTechnician/bert-base-uncased_LOGIC_Native") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f87bceb7649ee93184227607367593f096e63cbc1c6d181a40f579cbe0c0fb66
- Size of remote file:
- 5.27 kB
- SHA256:
- a12bfc4418724ba1877d000116649c60c00ece8e30371db1a9ec6db8c614e7c1
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