Instructions to use Team-PIXEL/pixel-base-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Team-PIXEL/pixel-base-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Team-PIXEL/pixel-base-finetuned-mrpc")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Team-PIXEL/pixel-base-finetuned-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab126aae83e28477cb049a9aa8e93bb37d23c3e4f552452e8f67a7659520c32f
- Size of remote file:
- 346 MB
- SHA256:
- dc503d2dcbd9c70536958eecfabfbc6342fcaf20489024e041d8a8cfc254d856
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.