Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_259 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_259 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_259")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_259") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_259", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a12436c93e96a7d9c5ff48b8abfc953432c642ff8e8912186312119f3d9a2ad0
- Size of remote file:
- 5.43 kB
- SHA256:
- 61bfc9b24cca694adb4bf628173181be95e2c26da883679a66a4e0f34e1b7a14
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.