Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use ppsingh/mpnet-adaptation_mitigation-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppsingh/mpnet-adaptation_mitigation-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ppsingh/mpnet-adaptation_mitigation-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ppsingh/mpnet-adaptation_mitigation-classifier") model = AutoModelForSequenceClassification.from_pretrained("ppsingh/mpnet-adaptation_mitigation-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9091afe81eea83ab65598c26cad87f3859b5eee653eee9248023922ed9eafdc9
- Size of remote file:
- 3.58 kB
- SHA256:
- dc438d2ed3f0e7df70f790352c3afccfd237b96e6550cf0c6d6510205c780b59
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