Instructions to use DreamingRabbit/CPGen-difficulty-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DreamingRabbit/CPGen-difficulty-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DreamingRabbit/CPGen-difficulty-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DreamingRabbit/CPGen-difficulty-classification") model = AutoModelForSequenceClassification.from_pretrained("DreamingRabbit/CPGen-difficulty-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e958bd6e837972af95fd53a32c151b7899a68924335efebdf70f9b0bd7d04e83
- Size of remote file:
- 6.03 kB
- SHA256:
- f78f3d33a36ad63f53515fd2d41eb9234ba33efc68e655e4fd4adf19540a83d3
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