Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use mtyrrell/CPU_Economywide_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtyrrell/CPU_Economywide_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtyrrell/CPU_Economywide_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtyrrell/CPU_Economywide_Classifier") model = AutoModelForSequenceClassification.from_pretrained("mtyrrell/CPU_Economywide_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be1b23fbd132b039bd8e78298990cb82d7ee36fb9268b9eb1a9281464582ab2f
- Size of remote file:
- 4.03 kB
- SHA256:
- a4712a6ac9f71359a95b9eb04374102f16c58c143984698bd21789061222754e
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