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:
- 45c5b4aa2b63bb9b25ee82772aa248481c1e549767a4e1f7fac1ba23705ef66e
- Size of remote file:
- 42.4 MB
- SHA256:
- 0ba1e7ee1566addba1f048ee6b756b605901704763c6a8eca35833ef29e55e22
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