Text Classification
Transformers
Safetensors
English
mpnet
edu score
data filter
text-embeddings-inference
Instructions to use pszemraj/mpnet-base-edu-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszemraj/mpnet-base-edu-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pszemraj/mpnet-base-edu-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pszemraj/mpnet-base-edu-classifier") model = AutoModelForSequenceClassification.from_pretrained("pszemraj/mpnet-base-edu-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45e19fdddddcd7eee7e543366f3d33086941d79c82456dd9a0dbb4503b474c7f
- Size of remote file:
- 5.3 kB
- SHA256:
- 64616dfde8eed804f3193de525a28dbd34808f3c5e9786fa31c75d797799482a
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