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:
- d6bb51e03f4e422382c5ff342253e1ce66376254b196e997e07de8227b0dc2a3
- Size of remote file:
- 2.67 GB
- SHA256:
- 68e8f362e6c6757d763f980fe96c736989fa17baed24ecdb3e24c38a49a3b08b
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