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", device_map="auto")# 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:
- 3eaf3bcb0d4041a741fb9ac1ec2c8ef42ca7ac492f4c1bda9888c1ca731aa34b
- Size of remote file:
- 438 MB
- SHA256:
- 6a9c6c899f92c1c413150fdb653411e70f035de2099921ffe74466e8b829d4bd
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