Instructions to use Shenzy/Sentence_Classification4DesignTutor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shenzy/Sentence_Classification4DesignTutor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shenzy/Sentence_Classification4DesignTutor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shenzy/Sentence_Classification4DesignTutor") model = AutoModelForSequenceClassification.from_pretrained("Shenzy/Sentence_Classification4DesignTutor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0df878426cd1d52e3bb60137a2f47194325a606d3db695e245aa21d0c715c68d
- Size of remote file:
- 1.42 GB
- SHA256:
- e7062047181416d00c7424172c2d49ab578b3eb5b44d60b153f53edd46b8ec8a
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