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:
- 8f787a0968745af8d6e9798aac47631ba76080c07f6c6980daf5b16d171685ae
- Size of remote file:
- 374 kB
- SHA256:
- cc79c5957798f90e14dcc0a2c7dd5260aff2e66e028471ad99a57afb1572472b
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