Instructions to use emaeon/trained_cppbert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emaeon/trained_cppbert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emaeon/trained_cppbert2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emaeon/trained_cppbert2") model = AutoModelForSequenceClassification.from_pretrained("emaeon/trained_cppbert2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bee2aa50869d17969770a04f399f4760abfe0514350d12782c32052d5eed03af
- Size of remote file:
- 499 MB
- SHA256:
- 2548a4b842535e36a5907ff5b73725caf82ae6659241dd7b81ff2ec2fffeba7b
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