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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3de4c678a23195a5a31746a4adf2c70d8151171694d97129e254f6fbc5f88a77
- Size of remote file:
- 6.56 MB
- SHA256:
- 5ca2f5641f3d79564a6585a3908dc9109194a2400fbb1f92089eb4c15429d71e
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