Instructions to use curious008/BertForStorySkillClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use curious008/BertForStorySkillClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="curious008/BertForStorySkillClassification", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("curious008/BertForStorySkillClassification", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("curious008/BertForStorySkillClassification", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8424fcff32afb6bc12a33fe07b39d704fd68675aeac28c01da697b6c0027187
- Size of remote file:
- 438 MB
- SHA256:
- 1d322777c24a6d50a9748b316d8a245cc336812a35f51a5477b0297e694b123f
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