Instructions to use wiorz/bert_small_summarized_defined with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wiorz/bert_small_summarized_defined with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wiorz/bert_small_summarized_defined")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wiorz/bert_small_summarized_defined") model = AutoModelForSequenceClassification.from_pretrained("wiorz/bert_small_summarized_defined") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e38a18d0bd414d0ac758061441335246abeb614f7867ae12549be716006675ae
- Size of remote file:
- 3.64 kB
- SHA256:
- 7dd94bb8be1c7119c67dcb0e3f4e78441a14e6787bbee0c62c670e0e20f9f48e
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