Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_205 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_205 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_205")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_205") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_205", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb689e59b8b1fe5fa4844064326c41047425a30367fb16c9b2fe625262c7cd0d
- Size of remote file:
- 1.11 GB
- SHA256:
- 97d804cda266a5718dfe6bf4d580b8113dedf00c04ead468bc7bc365b1eff478
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.