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:
- e6babe034cd7f7e00583d24a8a3158e818a4d1dec28f156306f548f3609ad25e
- Size of remote file:
- 1.58 GB
- SHA256:
- 6536132964eb9afe82894a1ed917153ce25ccedf17622ef904b4feca983cef2e
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