Instructions to use hf-internal-testing/tiny-random-BigBirdPegasusForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BigBirdPegasusForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BigBirdPegasusForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BigBirdPegasusForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BigBirdPegasusForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a69d8b8880a2fe975673d36b4ccb8bbf8388a658fd815c671587c018bd5b6090
- Size of remote file:
- 1.92 MB
- SHA256:
- fe1b40df7e8825709c0172639c47338a68d5622e9e3b6cc0fae516537cae738b
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