Instructions to use emaeon/trained_cppbert8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emaeon/trained_cppbert8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emaeon/trained_cppbert8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emaeon/trained_cppbert8") model = AutoModelForSequenceClassification.from_pretrained("emaeon/trained_cppbert8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c5acad566ddbdfb071060902b3291bc8badf3cf79fdb64c1e68b72de7bc971e
- Size of remote file:
- 499 MB
- SHA256:
- bf5bebe5496a8906c5eccfbfdba841c3d62723bac79ea8e12a838fd1a56a4967
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