Instructions to use hf-tiny-model-private/tiny-random-BigBirdForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BigBirdForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-BigBirdForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 225474f6ab5e5f031833255c08517a15ce1a9dced7967520d209737414d37faf
- Size of remote file:
- 6.55 MB
- SHA256:
- 97d40ad7a40faa3515724736176bf189f8367945e44cdac6d88359ae3f633edb
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