Instructions to use hf-tiny-model-private/tiny-random-CTRLForSequenceClassification 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-CTRLForSequenceClassification 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-CTRLForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CTRLForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-CTRLForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb978fbc6406a84e941255f5bc9c9f83bc02be0dc010995a650365f95d432b89
- Size of remote file:
- 42.3 MB
- SHA256:
- 226635decbc13430dc268341bea85a6ecef18613d3a9cd3c75702e2d99104008
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