Instructions to use hf-tiny-model-private/tiny-random-RobertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RobertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-RobertaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9b8f8cb6a387d7f82c897fb8e3bbc7cdceebeb96230748d24660e76dfc649a1
- Size of remote file:
- 372 kB
- SHA256:
- c7da1cf93cc39ea3d06bfab4fd10de7a0f5467ba8d6bdda41521150e48204820
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