Instructions to use hf-tiny-model-private/tiny-random-MegaForSequenceClassification 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-MegaForSequenceClassification 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-MegaForSequenceClassification")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegaForSequenceClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7f860cd3f3f7b0b3baa847d576188640d9a34f2fe17cd5d039de07263d26f25
- Size of remote file:
- 387 kB
- SHA256:
- da5d40388944033aca2f911c6045762730e1534f38c25c717bec224997694fa7
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