Instructions to use hf-internal-testing/tiny-random-RobertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-RobertaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-RobertaForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0eed0bfeb52c21a56747b826c2fd9d87066dfd79d3adf1cdaa2941baf58c233c
- Size of remote file:
- 372 kB
- SHA256:
- b27f96c7e83e44c8c47df20df9438274c3fe442e384fa04fe066c7af738bee2a
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