Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use tensor-polinomics/mrpc-bert-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensor-polinomics/mrpc-bert-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tensor-polinomics/mrpc-bert-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tensor-polinomics/mrpc-bert-test") model = AutoModelForSequenceClassification.from_pretrained("tensor-polinomics/mrpc-bert-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c51386c6f10485844b6709b809e0af88dc3e2f91df81a31263da5f12206c6489
- Size of remote file:
- 5.91 kB
- SHA256:
- 39805e636f0a5006f3d01924463fed14057f0d6a44a5dd4974c09e5c971cd8e9
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