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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1fb3461294d99a7dcd2b861a50b61129c0338aa5b383f0278b6bc32168e38e7
- Size of remote file:
- 3.96 kB
- SHA256:
- a528794617358372d640229426d84b0e1b184fc1e86091c35bc19a249c567b91
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