Instructions to use SushantGautam/bert-large-cased_accuracy-coverage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SushantGautam/bert-large-cased_accuracy-coverage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SushantGautam/bert-large-cased_accuracy-coverage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SushantGautam/bert-large-cased_accuracy-coverage") model = AutoModelForSequenceClassification.from_pretrained("SushantGautam/bert-large-cased_accuracy-coverage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab6cf6d4257b12113cb88d8f50b36948e67ae480942ff1de536034e44188c898
- Size of remote file:
- 5.05 kB
- SHA256:
- c59a6f17e1cb92d91510c03892313347a82f3cb06513ae7028daeb7934699fdf
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