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:
- d57c4df31d2370ba4f54a340fc88dc3de9f1b9bdb13a308c29bc46a388a22c7e
- Size of remote file:
- 411 kB
- SHA256:
- d418a3c22a6b50405e70ba88f4cf95ea843caf3804dff1feb7c058e5e298446c
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