Instructions to use hf-tiny-model-private/tiny-random-BigBirdPegasusForSequenceClassification 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-BigBirdPegasusForSequenceClassification 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-BigBirdPegasusForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdPegasusForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdPegasusForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12877d37e6d7b4c5c5ead4e25f797b80bb43c6b747e1631a6d91fb9647b9acb1
- Size of remote file:
- 1.92 MB
- SHA256:
- fe1b40df7e8825709c0172639c47338a68d5622e9e3b6cc0fae516537cae738b
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