Instructions to use MENG21/stud-fac-eval-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MENG21/stud-fac-eval-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MENG21/stud-fac-eval-bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MENG21/stud-fac-eval-bert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("MENG21/stud-fac-eval-bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51d4eea0e131293120448a3ea682b473163c07f372971073bda9465792b938b2
- Size of remote file:
- 438 MB
- SHA256:
- 0b2a6e41c2fd0108da30690b11a93496faac19bd7751cc5db5fcd380a0cbf74c
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