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:
- f3fe724514bf09d09a03c5c306d1e0b3899b4af221202ae4c658f7ddfe7f4f96
- Size of remote file:
- 3.64 kB
- SHA256:
- dff43d965fb6f91235e215c4bc8a632b661611e7ee3e80283923e2e8751e984b
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