Instructions to use ydshieh/tiny-random-DebertaV2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaV2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ydshieh/tiny-random-DebertaV2ForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaV2ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("ydshieh/tiny-random-DebertaV2ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41cd4207f762ee3249053d419fb51904002b8284df813094ec36550de3bed1df
- Size of remote file:
- 371 kB
- SHA256:
- d666700141393d7fb47ac5b476e2b76b1e17aca38a3b154b9a28d56eeecd7209
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