Instructions to use cruiser/bert_final_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/bert_final_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/bert_final_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/bert_final_model") model = AutoModelForSequenceClassification.from_pretrained("cruiser/bert_final_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 693c851e952b4d2005a331b9f203789a15cd2a7485edd380486002d70a5938cc
- Size of remote file:
- 876 MB
- SHA256:
- 8d07c52a4a2bf7efa945837447c4c27f5fd571060dfd5530b379e1c15fac6000
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