Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_229 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_229 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_229")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_229") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_229", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75d8e599038891766b40ad9aa892ddaa22f27066dea536bf1bf1d7dd83158296
- Size of remote file:
- 2.24 GB
- SHA256:
- c7d68885e25e5787cd8fefb1fe97b10f1c96fd84aa44c29716915edab80d5dd1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.