Instructions to use hf-internal-testing/tiny-random-RobertaPreLayerNormForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaPreLayerNormForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-RobertaPreLayerNormForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eceb85f505a4281bfb2f9e7cc5657d380b977c8e28e231a09e1f150dc426e3c
- Size of remote file:
- 355 kB
- SHA256:
- 0849e11e96e6dfde5f056931a80a63659f6186dd2a4da5f34479c94a140fc848
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