Instructions to use KalaiselvanD/distilbert_06_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/distilbert_06_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/distilbert_06_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/distilbert_06_1") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/distilbert_06_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e6a85a515ea6e7019b319a122dac60af69cf36098bf77ddc7c7373a72f874df
- Size of remote file:
- 4.92 kB
- SHA256:
- ee03ff0005efcc54a6d2d210b8602ff30abc2d9ef4526f3c60eca67e6f5c6e7f
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