Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_classifier_bsample_237 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_237 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_237")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_237") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_237", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdf71e24b606785ce24bf1cffe987d6a9e4562f5d6fdab69e381d6f6a65ff092
- Size of remote file:
- 5.43 kB
- SHA256:
- f889c69b159cb7702f8968c4332baf308e67b18913066004d8aabdb8de5656f9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.