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:
- b5606193ddaac054f81da97cd3830537dfd7eb8014a570349dde3b579da4cb2c
- Size of remote file:
- 5.43 kB
- SHA256:
- 7d1c5224909c4fd6b60c3b7e2cb86cfa9355bb7c0180ce77df06d68d926771b2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.