Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_222 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_222 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_222")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_222") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_222", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 051fec2595d591c1fd4c8451a9d4f5a35bc2c79763c45b96aa8cbcc8e652cdf5
- Size of remote file:
- 5.43 kB
- SHA256:
- 7f476b34603c040f3b2aed4cf39b59c1f3d7fa6f13069668a8b023c7d14b3725
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.