Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_209 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_209 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_209")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_209") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_209", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1aa1116c2be35ac6f00474e1759276010542a116d0a325d3a257c5359b3bd637
- Size of remote file:
- 5.43 kB
- SHA256:
- c2fc13791fb2b12a79325cd82564d22141d973df11a01f4690f18b87c099f9dc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.