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:
- 16b66f95bbb358b6026e95813783bca5fee9fcfd6c98e327102e22173dfeebec
- Size of remote file:
- 411 kB
- SHA256:
- 87a1ff0513cbea1199bdb15999c3cf559c80a95fa033bc4b7122019cd3f6d176
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