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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0f87cd75f2a64e2ebd4be99e4fea293e78c5ed7169a08f61be19c9595be412d
- Size of remote file:
- 6.56 MB
- SHA256:
- c7506f01539f8e96069c15ab34859de260ae768f87fa14f28c963901645751d9
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