Instructions to use Luciferalive/Bert_fine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luciferalive/Bert_fine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Luciferalive/Bert_fine")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Luciferalive/Bert_fine") model = AutoModelForSequenceClassification.from_pretrained("Luciferalive/Bert_fine") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08e7706f492c6452cf093657df4be61f3e28521effd2581526d0f21d3a1f9c53
- Size of remote file:
- 438 MB
- SHA256:
- f6d31b8c53ab4303e7bc4dc1f6ef4735c24d06ef3778f1b0dc479e9f04e92143
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