Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_120 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_120 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_120")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_120") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_120", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4a7e903917b579d6ea1ba7d087da2db14847a1c5cd47843c189fa42e08b5ae0
- Size of remote file:
- 2.24 GB
- SHA256:
- 7d7424f2376018bb3b7ec27f8a2fd79260a1c9c2d9b5ca918608347217ca1bcb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.