Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use mtyrrell/CPU_Mitigation_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtyrrell/CPU_Mitigation_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtyrrell/CPU_Mitigation_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtyrrell/CPU_Mitigation_Classifier") model = AutoModelForSequenceClassification.from_pretrained("mtyrrell/CPU_Mitigation_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3bd2674259ae2d386f420fbef956e35915e2dfa5ac85423e85a1ab8dfb31700
- Size of remote file:
- 4.03 kB
- SHA256:
- 62c2247f76cf7af0ebabe2c0973995b11292339e0c2118e267ae9a1b13e24e34
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