Instructions to use hf-internal-testing/tiny-random-MegaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MegaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MegaForSequenceClassification")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MegaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c022138cfd2a8752c78002fc5392043e843345761aa3c663f626472f709b2130
- Size of remote file:
- 411 kB
- SHA256:
- 56581c9bee17b6185d43047a3ad306eca9c57a031c86aa6650f60f5344e1351e
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