Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use mtyrrell/CPU_Conditional_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtyrrell/CPU_Conditional_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtyrrell/CPU_Conditional_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtyrrell/CPU_Conditional_Classifier") model = AutoModelForSequenceClassification.from_pretrained("mtyrrell/CPU_Conditional_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21f3e8c3548177e9c0003fb231c2c0815fb895a25a80a1e789a89116b12f91ba
- Size of remote file:
- 4.03 kB
- SHA256:
- 69bf2e1c946312a7d9c7251f7c66b38dd1e00bf518cab3324781054a297b1a18
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