Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_032 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_032 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_032")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_032") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_032", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a43af95d2edd33a8a4e9e419db5d1084980c711df3dce7eccc3e172ea7687525
- Size of remote file:
- 669 MB
- SHA256:
- 23c4fcc0c79a4cb4c5291cbc198bc76bc23cce740ce17e780612f0fda62bb230
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.