Instructions to use fredymad/bert_laxo_2e-5_16_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/bert_laxo_2e-5_16_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/bert_laxo_2e-5_16_10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/bert_laxo_2e-5_16_10") model = AutoModelForSequenceClassification.from_pretrained("fredymad/bert_laxo_2e-5_16_10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d04276ed6b9e2e555f2486cc96b2d5cc7cc0dab698605b6311a0237288039274
- Size of remote file:
- 438 MB
- SHA256:
- 2278b105f8b2043df8197891c2f5bea987d55c50a4fe437e372ddf1839dd55c2
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