Instructions to use justinlamlamlam/softwareengineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use justinlamlamlam/softwareengineering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="justinlamlamlam/softwareengineering")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("justinlamlamlam/softwareengineering") model = AutoModelForSequenceClassification.from_pretrained("justinlamlamlam/softwareengineering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6903f1a524e4ecc54ea15c6c1a4dc905c36f7359c6c8bb15852698a78aef65b
- Size of remote file:
- 438 MB
- SHA256:
- d67639251cc80db7b1a3af57ef448cfa5420533d841a07b4c11f4e5dec344339
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.