Instructions to use emaeon/trained_cppbert6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emaeon/trained_cppbert6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emaeon/trained_cppbert6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emaeon/trained_cppbert6") model = AutoModelForSequenceClassification.from_pretrained("emaeon/trained_cppbert6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dda4891d0a488a60179110e32d42a0ca3cfb9de5f48c4f79ddb21fcace91130
- Size of remote file:
- 499 MB
- SHA256:
- 197aa55d6df3d7b2c8bc5c5b83684cba48baf8fc8de669ce12218023347564ad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.