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:
- 7e9257bda86a905e928d6500a72138a8f4f6abd53f4eae42950c671348b86c9a
- Size of remote file:
- 3.31 kB
- SHA256:
- ee6ed6f4e69540a75769b4aabe3ef00f67aaf8c8c36f11253ee46f07f2b8a1d8
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