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:
- 7de57ccf8b122973985c82503f6f27056632a1c0675411e8d19871d08c3caf55
- Size of remote file:
- 438 MB
- SHA256:
- 6f8c8d9fc94fd5bac0f2d4781f8020c38bef46e2483adb26abe39453f179c47b
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