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:
- 8d73f5b4e3f735eca18e783db5f1e92e46e2e17b7494ee769eea1945258b9ee2
- Size of remote file:
- 411 kB
- SHA256:
- 94173b279fddc7f62fb6ad22642d92dbc4e948781b80f8b2072184b647fe7010
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