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:
- ee558529fb37858976b97a324ebf68302ae6035de596beb143112076e6ddb874
- Size of remote file:
- 467 kB
- SHA256:
- 21ebd20fff3a61f3043373f26fa61184cf0adc378c239429b7d53d262f22e4d3
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