Instructions to use rajendrabaskota/bert-base-dataverse-2023 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rajendrabaskota/bert-base-dataverse-2023 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rajendrabaskota/bert-base-dataverse-2023")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rajendrabaskota/bert-base-dataverse-2023") model = AutoModelForSequenceClassification.from_pretrained("rajendrabaskota/bert-base-dataverse-2023") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ad071837e2425bbba2a4d599aa644e5934e32fa497302e85cd58eba28e3b55f
- Size of remote file:
- 438 MB
- SHA256:
- 900eb28b8ac988573fd841085978f81c4ae0db873d74cc35ae562de4696f6a22
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