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:
- c8eb4b886863046cf89c4ab68208b5031752a990c8ce24d89e0f4747ab19c096
- Size of remote file:
- 3.9 kB
- SHA256:
- 17f8aac72eca16127dafccb0ee79a46ea2373544d9c947c76162d1326b1a253c
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