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:
- 735ed3e6cbdd4c8557be6056df7bdcf751dbe4d60f839c3c23855f08c5b4420a
- Size of remote file:
- 4.93 MB
- SHA256:
- e718f819d3d9aa9ad3183b2fef8496fa0a6d9dce0af6b42f5b00370a27ba0ddb
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