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:
- c03662b106b26a7415f1ac6628b3e75d61fc8365abb6a42df79e31b2482735e8
- Size of remote file:
- 50.7 kB
- SHA256:
- 296b19996d77cf2967703c6a9768fd89447077a38a52d2caad1148637e4011a7
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