Instructions to use Mahmoud8/ernie-m-base_pytorch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/ernie-m-base_pytorch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/ernie-m-base_pytorch")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/ernie-m-base_pytorch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bf40f6705f014e723ff812371824a6d70a530095a85936d39c5e7d6bd949c7e
- Size of remote file:
- 1.11 GB
- SHA256:
- a28a4d9c9650147a237e511eb01e3af92c6969d98710408920dde72d2696a2c7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.