Instructions to use cmlformer/bertCLS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmlformer/bertCLS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cmlformer/bertCLS", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cmlformer/bertCLS") model = AutoModelForSequenceClassification.from_pretrained("cmlformer/bertCLS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d3808fe588c27b3f0644f4f554d413b3f175d2875739b6d665e2744669ff517
- Size of remote file:
- 131 MB
- SHA256:
- d36b2473c944fb905eb6eca9bf6b8f90657f6cbe0612bc4e85d8ad1c242ee7ec
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