Instructions to use Sayan01/DBERT2_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/DBERT2_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/DBERT2_sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/DBERT2_sst2") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/DBERT2_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aef56364f749d42d774acf2802cdea73f2a3fe741a6dfc0010a70660aead9676
- Size of remote file:
- 325 MB
- SHA256:
- 94ecf8e57761d0812502d78eab8c2ff9070498e10d0bfd783c40366f153b573e
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