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:
- 1644fbc717c1e2b322ac0f2138ac29bd153758b55190081dc500ca5a8aa7e200
- Size of remote file:
- 3.17 GB
- SHA256:
- 99382c52379ffa2a96b6417114180b7cd678c9380cc079b37f4f8ce9fce09158
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