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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- add52c629049a72598b561237c4a7ee86f72bfbea3d5edcf67ca46515454771f
- Size of remote file:
- 477 kB
- SHA256:
- 919d47a30cbc800b05207f7697b38489e6c84953e276e1a6e86a9723ecc64555
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