Instructions to use AIWizards/MultiPRIDE-DualEncoder-LPFT-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIWizards/MultiPRIDE-DualEncoder-LPFT-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIWizards/MultiPRIDE-DualEncoder-LPFT-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIWizards/MultiPRIDE-DualEncoder-LPFT-es") model = AutoModelForSequenceClassification.from_pretrained("AIWizards/MultiPRIDE-DualEncoder-LPFT-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fb6adf9d18fe984e4021363a551e99db396afc10f8c265b08859effa5b2e21f
- Size of remote file:
- 5.97 kB
- SHA256:
- 6123d693a1672038386f5e9b4f0e796cc99675ffe4689b05d78b53f69fe8dbc9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.