Instructions to use hf-internal-testing/tiny-random-RoFormerForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoFormerForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-RoFormerForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoFormerForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-RoFormerForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2460605d4f451658ea70d3129a2cb722c6f03465a9feb9ab25da65d656499054
- Size of remote file:
- 6.57 MB
- SHA256:
- 09aa46ddd4d7e613cf8679ebb50f97677d94eae059f8663199340f28ce1cabfc
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