Instructions to use MENG21/studfacultyeval-DISTILIBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MENG21/studfacultyeval-DISTILIBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MENG21/studfacultyeval-DISTILIBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MENG21/studfacultyeval-DISTILIBERT") model = AutoModelForSequenceClassification.from_pretrained("MENG21/studfacultyeval-DISTILIBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76708864ca4cff2e6a245d0e6044939b5fce470c47b68c26df3885bd126db237
- Size of remote file:
- 438 MB
- SHA256:
- d0b1f3dff5846baed857567ad59a16564a2658e8f691fa3bb031831bf26d037c
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