Instructions to use Cheykong/HRVibeCheck-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheykong/HRVibeCheck-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheykong/HRVibeCheck-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheykong/HRVibeCheck-BERT") model = AutoModelForSequenceClassification.from_pretrained("Cheykong/HRVibeCheck-BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9425ab5d8ac8b59e54298d518024ef02f3d015317398543e31fd1fba0d78d0f
- Size of remote file:
- 5.2 kB
- SHA256:
- 4056c35c13cc2229e2dcebb7aac27fd1ec3f86527d9474c5c17ce3b5626536f3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.