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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 078610e85e63b08fa6e1529c96290bec8d5ca7914e0e3a02431b58165cdd45e6
- Size of remote file:
- 438 MB
- SHA256:
- 5bf6b669a711d4b646723f9efbfd79f81ddc34109feff085581b48bf7f077da2
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