Instructions to use hf-internal-testing/tiny-random-BigBirdForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BigBirdForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BigBirdForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BigBirdForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BigBirdForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 732805b93417ea960fc6f8de511a1368cced8f34d532d9d4969ee696cd2032de
- Size of remote file:
- 6.55 MB
- SHA256:
- 52a8d019477c8e7a813e4aa809b184e6a22d310ef106ce126f2155ec66254bae
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