Instructions to use vishnun/codenlbert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vishnun/codenlbert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vishnun/codenlbert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vishnun/codenlbert-tiny") model = AutoModelForSequenceClassification.from_pretrained("vishnun/codenlbert-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e90e9e3cfabef11d7df729bf67ff151325ea059978737016c3c9c3192a52de1
- Size of remote file:
- 3.96 kB
- SHA256:
- 8f1444d4567d14e283b62f4bc95e5ec30b616241635608a95c1178577ab7aa12
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.