Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_103 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_103 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_103")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_103") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_103", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac41b84972c250c4a8d65138d905228ff5a6549cbc0a0d18a94b375962999aa2
- Size of remote file:
- 1.11 GB
- SHA256:
- 651382b2239ddd487fe52752adcfaea8a4f7d136890ab4370364dec219353a19
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