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:
- ff1ad1ab30549f78315307e7e1d7b1d7689534533c15ca3ff80c035541ba65ea
- Size of remote file:
- 3.96 kB
- SHA256:
- 2b97f9464466a6044075aa463193215dbfdc10e9a08da4c04e143b8bd68a1d39
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