Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use P3ps/test-trainer-glue-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use P3ps/test-trainer-glue-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="P3ps/test-trainer-glue-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("P3ps/test-trainer-glue-mrpc") model = AutoModelForSequenceClassification.from_pretrained("P3ps/test-trainer-glue-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 365b694b953a09858f9c1d32e72ada5037c720c733c1145b47413484ae6623fc
- Size of remote file:
- 438 MB
- SHA256:
- e50899db5935ad6ee97515951be9bf3160cfc5ead12ea0c5031916bb729d6a2a
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